1. Introduction
It is well known that aerosols play an important role in atmospheric radiation transfer and radiation climatology (e.g., Kondratyev 1991; d'Almeida et al. 1991). Under cloudless conditions the inflow of solar radiation is determined by the total atmospheric transmission function TΣ = TATWTXTCTR, which depends on the aerosol TA and the water vapor TW components, as well as on the transmission of other gases: TCTXTR (CO2, O3, Rayleigh scattering, etc.). An important feature of the main components TA and TW is that they are very sensitive to regional and synoptic variations. The contribution of other components can be treated as constant or calculated with a reasonable accuracy from modeled mean data for a particular season and latitudinal zone.
The continental network operations (Gushin 1988; Forgan et al. 1994) allowed us to obtain extensive empirical data to reveal the features of the spatial and temporal variability of the spectral and integral atmospheric transparency, aerosol optical depth (AOD), τA, and columnar water vapor. The knowledge of the optical characteristics of the oceanic atmosphere is less complete and reliable since it is based on scanty data from shipborne measurements and coastal stations data that are subject to continental influences. Judging from the review paper (Smirnov et al. 1995b), there were, in all, about 50 expeditions in the world's oceans that investigated AOD. In a majority of these expeditions the data were obtained during a few days or for a narrow spectral range (1–2 wavelengths). Even for the most visited area, such as the Atlantic Ocean, the total bulk of data is comparable to a 2-yr observation cycle at a single continental station. In this connection, let us dwell on the objective methodic shortcomings typical of marine studies of the atmospheric transparency.
First, the difficulty of onboard ship measurements leads to an even greater discontinuity of the observation series, as compared to ground-based measurements. If we estimate the degree of “regularity” as the ratio of the number of days of observation to the total period of measurement, then for the majority of investigations this value will be from 0.3 to 0.6. Second, the data obtained in the course of navigation are a cumulative result of the spatial and temporal variability of the atmospheric transparency. Last, individual marine investigations, contrary to uniform network observations, use different wavelength ranges and techniques to measure and calculate the τA. All these make it difficult to compare and generalize the isolated data of different expeditions.
Considering the problem of the spatial and variability of the atmospheric transparency over the ocean, one cannot fail to mention the results of global spaceborne observations by means of the Advanced Very High Resolution Radiometers (AVHRR, the moderate resolution imaging spectroradiometers, and the Sea-viewing Wide Field-of-view Sensor (e.g., Mishchenko et al. 1999; Swap et al. 1996; Kaufman et al. 1997; Tanre et al. 1997). Though these investigations are important and promising, the error of reconstructing τA from the satellite data amounts to 0.03–0.05 (Rao et al. 1989; Ignatov et al. 1995; Tanre et al. 1997), and the results are usually related to one wavelength. Thus they cannot reveal the regional and meteorological features in the spectral behavior of AOD.
The most detailed shipborne investigations of τA were carried out in the 1970s through the 1980s by two groups: Barteneva et al. (1991) and Shifrin et al. (Shifrin et al. 1980; Volgin et al. 1988; Yershov et al. 1990; Villevalde et al. 1994; Smirnov et al. 1995a; etc.). Recent multiwave investigations of
Long-term optical investigations of the atmosphere were carried out by the authors of this paper over a significant portion of the Atlantic Ocean in 1989–96. These investigations, to some extent, fill the gap in our knowledge of the transparency of the marine atmosphere (Sakerin et al. 1991; Sakerin et al. 1995; Kabanov et al. 1997b; etc.). The data obtained were also used to validate the results of satellite observations (Ignatov et al. 1995). In our experiments we used the sun photometer in the wavelength range from 0.37 to 1.06 μm (part of the data was derived in the range of up to 4 μm). In addition to AOD, the atmospheric columnar water vapor W was measured using the differential technique in the absorption band 0.94 μm. In the present paper we generalize our previous results related to the spatial distribution of transparency and the features of spectral behavior τA (λ) over different areas of the ocean.
2. Experiment and methodology
a. General characteristics of the experiments
Measurements of the atmospheric transparency carried out in five expeditions cover the greater part of the central and North Atlantic (latitudinal zone from 10°S to 60°N), as well as the North and the Mediterranean Seas. Experimental sites and the routes of the research vessels (Fig. 1) give a general idea of the operational locations. Particular significance was attached to the continuity of the observation series in the course of each day and the total period of measurement. Table 1 shows that the total array of measurements amounted to 264 days and the degree of regularity of observations (except for 1989) was maintained at the level of 0.9. Hourly observations were performed in 10–50-min-long series, provided there were favorable atmospheric conditions (cloudiness, precipitation, etc.). Preliminary data analysis was limited to individual geographical regions without accounting for the peculiarities of the spatial distribution of aerosol over the ocean. In the course of revealing the pattern of the spatial distribution
b. Instrumentation
The first measurements (1989) used a simple photometer described by Korotaev et al. (1993). Later, a few modifications of the multiwave automated sun photometers specially designed for marine researches were introduced at the Institute of Atmospheric Optics (Kabanov et al. 1993; Sakerin et al. 1996). Let us briefly describe the base variant of the device (Fig. 2).
Shipborne conditions of operation dictated the implementation of sun photometers in two separate parts: the control and recording system (A) stationed in the laboratory, and the remote optical and electronic unit (B) on a two-coordinate rotating table that can be placed on the upper deck at the distance of up to 20 m away. To reduce the influence of external factors (humidity, temperature, electromagnetic stray signals), the optical and electronic unit is put in a shielded thermostatic moisture-proof case. The photometer includes the automated sun tracking system, shortwave (0.37–1.06 μm) and longwave (2–4 μm) measurement channels. The main parts of the shortwave channel are a color-correcting inlet window (for spectral equalization of the signals), a quartz lens, and the photodetector. The hybrid integral photodetector includes a silicon photodiode and an amplifier with a switchable amplification coefficient. The longwave [infrared (IR)] measurement channel consists of an inlet window, a germanium lens, and a pyroelectric detector with a selective amplifier. The wavelength tuning is performed by a continuously rotating barrel with interference filters and a synchronization scheme that produces the service signals. The specifications of the photometer is given in Table 2.
The sun tracking system consists of a four-sector photodetector placed at the lens' focus, and the electronic scheme that drives the rotating table. The recording system includes the control unit, the analog–digital converter and a personal computer. Measured and service signals are fed into the computer during the operation. Exact time and navigation data from the global positioning system are input through the serial port.
The measuring and data processing program performs the following basic operations: (a) sorts out the signals by spectral channels with reference to the time and coordinate readings; (b) accumulates and filters the signals and calculates the optical air mass; (c) performs intermediate calculation of
c. Methodology
At the first stage of our investigation, in order to find
In the IR “transparency windows,” even when working with a high spectral resolution, it is practically impossible to single out the bands that are completely free of absorption. It indicates that a more thorough calculation of absorption is required, which would account for the change of concentration of “variable” gases (H2O, O3) and overcome the calibration difficulties due to the nonlinear dependence of ln(Uλ) and ln(
The necessity to use Eq. (3) in calculations was dictated not only by the finite character of the photometer spectral resolution but also by the significant effect of the “wings” of the spectral transmission of the interference filters. The estimation showed that the negligence of the latter factor especially affects the spectral channels near the absorption bands.
Approximations for
Note that the transmission functions of separate atmospheric components along with their air masses Mi are calculated independently [Eqs. (4)–(7)]. Therefore, the technique considered makes it possible to relatively simply extend the measurements to zenith angles of about 85° and take into account the individual dependencies Mi(Z) (Sakerin et al. 1997). Thus, there is no need to do more complex iteration calculations (e.g., Forgan 1988).
d. The calibration and accuracy of the retrieved τAλ
Thus, the iteration algorithm (10) substantially simplifies the calculation procedure for qualitative data U0λ. The essential requirement here is the accumulation of a sufficiently long series of observations, including measurements made during high atmospheric transparency. For this reason, the main difficulty we encountered during our cruises was in providing long-term stability of the photometer operation under the complex influence of the environment (ship rolling, vibration, wave spray). In two cruises (1991 and 1995) we had to perform recalibration because of equipment failure. To reduce the risk of a short “uncalibrated” array of data, in the last expedition we used the reference lamp source of stable radiation.
The accuracy of determination of
3. Results and discussion
There are possible differences when comparing with the results of other authors because of different techniques applied to calculate α and β (Cachorro et al. 1987; Cuomo et al. 1993; etc.) We used hourly mean and daily mean spectra of
The spatial variability of
a. Genetic zoning
In the existing climatic zoning methods one can single out two classification groups: genetic and “sign” (Samoilenko 1983). Obviously, aerosol as an element of a climatic system can be subjected to analogous classification. For the oceanic areas, genetic zoning appears preferable since it reveals the main processes forming the atmospheric physical fields and enables us, in the case of insufficient data, to extend the revealed features to less studied areas. The atmospheric circulation and peculiarities of the underlying surface play an important role in many genetic classifications (Alisov et al. 1974; Flohn 1957; Samoilenko 1983; etc.). The type of underlying surface also determines the majority of aerosol sources and the aerosol spatial distribution depends on the air masses transport. The following feature is essential for the atmosphere over the ocean.
Microphysical and optical investigations of aerosol over the ocean (e.g., Kondratyev et al. 1983; Reddy et al. 1990; Barteneva et al. 1991; Smirnov et al. 1995a) showed that in spite of the homogeneity of the underlying surface (the generator of marine aerosol) and the smooth variation character of meteorological fields, the variations of the aerosol characteristics are significant and in many respects are influenced by the intrusion of different types of continental aerosol. One can draw an obvious conclusion from this fact that the transfer of continental aerosol leads to spatial inhomogeneities of AOD over the ocean. Thus, the classification of the aerosol fields should take into account the combined effect of two principal factors: the sources (types) of aerosol prevalent in each latitudinal zone and the prevalent circulation of air mass that determines the depth and the direction of aerosol emission into the oceanic atmosphere. For this reason, we did not use our optical data for the genetic zoning, instead we leaned upon the results of investigation of the wind characteristics (Roll 1965; Kool 1975) and the aerosol composition in different areas (Prospero 1979; Kondratyev et al. 1983; Hoppel et al. 1990; Fitzgerald 1991; Barteneva et al. 1991; etc.). The atmosphere over the major space of the ocean is characterized by the variety of circulation, climatic conditions and aerosol sources. Nevertheless, it is sufficient to select three principal zones (temperate, tropical, and equatorial) in the latitudinal division (except the Arctic), which simultaneously take into account both the difference in aerosol sources and transfers.
In the temperate latitudes a finer aerosol prevails over the sea-originated aerosol (e.g., Barteneva et al. 1991). A narrow littoral zone (LZ) can be marked out along the continental border where the breeze circulation mixes up the continental and sea aerosols, and thus enriching the latter with the fine fraction. The extension of this area from the coast can be estimated by tens of kilometers. The developed cyclonic activity typical of these latitudes and the westward transfer provide subsequent migration of continental aerosol into the ocean. Moving farther into the ocean, the air mass loses continental aerosol while the concentration of sea aerosol increases. So one should separate the near-to-continent (NC) areas and the most remote midocean (MO) areas.
Our optical data (Fig. 10) confirms the redistribution of fine and coarse aerosols as one moves farther from the continent. A large concentration of fine aerosol in the coastal zone determines the high selectivity of the spectral dependence of τA(λ). As the distance from the coast increases, the spectral behavior becomes more flat because of
At tropical latitudes the stable trade wind transfer accompanied by the emission of coarse dust aerosol from the Sahara Desert is predominant. It is well known from the coast-based, shipborne and spaceborne investigations (e.g., Prospero 1979; Hoppel et al. 1990; Barteneva et al. 1991; Swap et al. 1996) that the content of the Sahara aerosol gradually decreases, but still can be traced up to the coast of America. The inversions and relatively high transfer speed in the layer from 2 to 4 km, which is characteristic of the trade wind zone (TW), favor this fact. One can assume based on the aerosol characteristics that the TW reaches the west coastal areas of the Atlantic. Correspondingly, the MO area narrows in the southward direction and is restricted to the TW. The TW area, most rich in dust aerosol (eastward of 35°W), is known in literature as the “Dark Sea” (DS). The natural southern boundary of DS and TW lies in the intertropical convergence zone (IC), for which the annual mean position is near 7°N (e.g., Kool 1975]. The IC axis, as well as the trade wind axis, are deflected from east-northeast to west-southwest.
The mixed areas, the Canary Islands (CI) and the Mediterranean Sea (MS), should be marked out in the northeast of the tropical zone. These areas, depending on the seasonal circulation, are alternatively affected by the emission of fine and coarse aerosols from Africa and Europe. The change of circulation is caused here by the proximity of the northeast trade wind to the Azores anticyclone—one of the main centers of atmospheric activity.
At last, in the southern part of our investigation area there is located the equatorial zone or IC. This zone has the following typical geophysical conditions: calm wind, developed convection, filtration of continental aerosol by cloudiness, and frequent precipitation (e.g., Samoilenko 1983; Barteneva et al. 1991). All these conditions form a character of aerosol turbidity different from the neighboring trade wind zone.
b. Sign zoning
To confirm the results of genetic zoning, we further applied the sign classification. In the sign classification, the zones are chosen based on several directly measurable quantitative characteristics of the atmosphere (Samoilenko 1983). Pertaining to AOD (Volgin et al. 1988) it was shown that in order to reveal optical differences in the atmosphere over different areas, it is sufficient to consider two signs: the value of
The zoning procedure included two stages. First, the isolines of the characteristics were drawn on the map (Fig. 12). The values of
At the second stage we determined the zone boundaries. The selection criterion for the MO zone was the fall of
The quantitative characteristics of AOD for the separated areas of the ocean are presented in Table 4. For different areas the samples obtained statistically differ in at least one parameter with the confidence interval of no less than 0.9. Calculating the characteristics of
Table 4 gives a good picture of the differences between the aerosol provinces with regard to the mean values of AOD, parameter α, and the variation coefficients Vτ. The enhanced turbidity near the continents (NC, DS, CI) is obvious. Also there is no need to comment on the fact that the Ångström parameter grows when approaching Europe (America) from the oceanic values 0.6 and approaches the continental values [α ≈ 1.3–1.6 (e.g., Barteneva et al. 1991; Halthore et al. 1992; Cachorro et al. 2000)]. Approaching Africa, the turbidity increases due to the enrichment by coarse dust particles. So the variations of the parameter α are less significant. The areas with the developed cyclonic activity (MO, NC, CI, and MS) are characterized by the maximum relative variability of the value of
Our calculations of statistical characteristics (Table 4) did not use the measurements taken in 1991, 1–3 months after the Mt. Pinatubo eruption (Sakerin et al. 1993; Zyev et al. 1997). The characteristics of
τAλ τAλ The results obtained in the MS zone are not sufficiently representative because of scanty measurements made in this area. The values of
τAλ
c. Statement and comparison of the results
A good confirmation of the reliability of the performed zoning is the agreement between the results of genetic and sign classifications. The ranges of values of
To estimate the validity of the spatial distribution model of the aerosol turbidity, we will compare our data with the results of other investigations. We will consider mainly the investigations in which the data are most reliable from the viewpoint of statistical and spectral provision (Table 5). The comparison shows that our data fall into the middle range of values published by other authors. Thus, in the MO area the mean values of
The scatter of the mean values in a relatively small DS area
Still the question persists: What time period does the obtained characteristics of
d. Spectral behavior of τAλ
The spectral behavior of τA(λ) in the shortwave range manifests itself in monotonic decrease as the wavelength increases. The empiric Ångström formula [Eq. (11)] is the most widespread form of analytical description for the spectral behavior of AOD (e.g., Ångström 1961; Tomasi et al. 1982; Hoppel et al. 1990; Cuomo et al. 1993). The power dependence of τA(λ) is caused by the fact that the submicron aerosol particles, whose relative size (2πr/λ) fall into the beginning of the region of the Mie extinction efficiency factor Q(r, λ) ∼ λ−1, usually make the principal contribution into scattering. For coarse aerosol Q(r, λ) ≈ 2, and the spectral behavior is practically neutral. Redistribution of the relative contribution of fine and coarse aerosol particles in the atmospheric column directly affects the spectral dependence of τA(λ). One can approximately assume that the parameter β depends on the coarse aerosol density, and α characterizes the concentration of fine particles relative to coarse ones.
The marine atmosphere as compared with the continental one has less concentration of fine aerosol (Kondratyev et al. 1983; Barteneva et al. 1991; Fitzgerald 1991, etc.), so the spectral variations of τA(λ) are not very significant. Nevertheless, on average, the monotonic decrease of
There might be some doubts about the fact that the minimum values of
The spatial distribution of the statistical characteristics of β (mean value, standard deviation, max) follows the distribution of the values of AOD with maximum in the trade wind transfer zone (TW, DS). In the areas far from the dust emission, the mean values of β, as well as of
e. Spectral behavior of τAλ
There were only isolated cases of investigation into the atmospheric transparency over the ocean in the spectral range above 1 μm. At least, we are aware of two publications by Wolgin et al. (1991) and Villevalde et al. (1994) in the range of 0.46–1.64 μm, related to shipborne investigations in the Norwegian Sea and the Pacific Ocean. We made measurements of
Figure 14 shows, as expected, that in the longwave range, the spectral dependence of τA(λ) changes from power to neutral. For the sake of comparison, the results of other investigations in similar conditions are shown in the same figure. Note that the data obtained in the Dark Sea are close to the values of τA(λ) obtained during dust emissions in Senegal (Tanre et al. 1988) and in the south of France (Deuze et al. 1988). The measurements in the Norwegian Sea (curves 1 and 2) were carried out relatively close to land, so the obtained data are intermediate among the spectra of τA(λ) obtained in the MO and NC areas.
The parameters in the modeled dependence (12) calculated by the least squares method enable us to estimate the contribution of fine and coarse aerosol for different regions (Table 6). In particular, the value, γ = (mλ−n/τc), characterizes redistribution of the effect of two fractions in the wavelength range from 0.37 to 1.06 μm. Judging by the high values of m and γ, the DS area is characterized by a large content of both coarse and fine aerosol. The regions were divided into three groups according to the degree of selectivity of τf(λ): minimum values of n are observed in the trade wind zone; intermediate in CI, IC, and NC areas; and the maximum values are in MO area. Insufficient data do not allow us to unambiguously interpret this fact. We can only suppose that the fine aerosol mode in the clear air of the MO area is most narrow and is shifted to a smaller size.
To determine the spectrum of τA(λ) which actually corresponds to the background conditions, rare cases of “surges” of the values τA in the shortwave range were excluded from the bulk of data, and the statistics of the parameters m0 and n0 was calculated (Table 7). From the statistical characteristics one can judge about the content of two main fractions: large marine particles and fine, apparently, sulfate aerosol. One can consider Eq. (13) together with corresponding values of m0 and n0 as a few-parameter model of τA(λ) for the background oceanic atmosphere.
f. Integral transparency of the atmosphere
The mean spectra of
As before, the coarse component
4. Conclusions
During our research work we developed a multiwave sun photometer, along with algorithms and software, suitable to carry out continuous real-time measurements of the marine atmosphere transparency and AOD in a wide spectral range. The experience of a number of sea expeditions confirmed the efficiency of the chosen approach to the measurement even under most complex conditions—sun irradiation measurements through small and fast-changing cloud breaks, complicated by the ship's rolling and maneuvers.
In this paper, supported by previous results, we have discussed main patterns and regularities in the variability of atmospheric transparency over the ocean. A stress is put on the necessity of regional approach to its properties. The spatial inhomogeneities of
The parameters of empirical dependencies τA(λ) determined for the shortwave range provide a qualitative description of the mean spectral behavior of atmospheric AOD and its variability in different regions. The mean values of the parameter α lie in the limits from minimum 0.3 in the trade wind zone to maximum 1.1 near the continents at temperate latitudes. The features of the spectral dependence of τA(λ) are considered in the extended wavelength range, and the expedience is noted of its description by the sum of two components related to fine and coarse aerosol. Assessment of the effect of two fractions on the formation of atmospheric AOD shows that coarse aerosol plays predominant role over the greater part of the ocean. The contribution of fine aerosol is prevalent only near the continent at temperate latitudes. Concerning the total atmospheric transparency, the aerosol component TA is shown to be most subject to variation. The spatial variability of the atmospheric transparency over the Atlantic is characterized by the following mean values (at Z = 60°): TA = 0.5–0.87, TW = 0.77–0.84, and TΣ = 0.33–0.61.
The quantity of experimental data still remains insufficient to develop qualitative empirical models of aerosol atmospheric turbidity over the ocean which would account for seasonal variations. So we do not claim that our model is complete; we rather see our main goal in the formulation and substantiation of the principles of the ocean zoning, which will allow for systematic analysis of isolated results obtained in different areas. Comparison of the mean characteristics of τA and α with the data of other authors gives us ground to consider that our investigations derived the most substantiated estimates of spectral AOD for the central and the North Atlantic.
Acknowledgments
The authors would like to thank academician V. E. Zuev (Institute of Atmospheric Optics, Tomsk, Russia) and the Director of Instituto Canario de Ciencias Marinas (Gran Canaria, Spain), who were heads of the expeditions; A. M. Sagalevitch (Institute of Oceanology, Moscow, Russia); and G. K. Korotaev and N. A. Panteleev (Marine Hydrophysics Institute, Sevastopol, Ukraine), who favored the long-term investigations of the spectral transparency of the atmosphere over the Atlantic ocean. We especially thank L. L. Stowe, P. Clemente-Colon, and A. M. Ignatov (Satellite Research Laboratory, NOAA/NESDIS, Washington D.C.) for the help in the investigations and the financial support of the 1994 expedition.
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The routes of five expeditions (sites of the most intensive observations are circled)
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Scheme of sun photometer SP-3
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Data display during experiment (short time decrease of the signals is related to a semitransparent cloud)
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Illustration of the dependencies of Θ(
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Example Langley plots for several wavelengths (1996)
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Relative differences of calibration constants for different wavelengths
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Difference in the determination of
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Correlation between
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Examples of (a) latitudinal and (b) meridional dependencies of
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Transformation of the spectral behavior of τA(λ) at temperate latitudes when moving out of the continent
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Location of the “aerosol areas” as result of the genetic and “sign” (dotted line) classification
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Isolines of the spatial distribution of
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Spatial distribution of AOD of the atmosphere obtained from the satellite data
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Mean spectral behavior of
Citation: Journal of the Atmospheric Sciences 59, 3; 10.1175/1520-0469(2002)059<0484:SIATSB>2.0.CO;2
Information about oceanic expeditions (N is the duration of measurements, n is the number of the days of measurement, n/N is the observation regularity degree, and k is the number of hourly mean readings)
Main characteristics of the multiwave sun photometer (1995 version)
Comparison of Uoλ calculated by different methods (example of the results of 1994)
Mean values and variation coefficients V of
Mean values of
Parameters of the dependence τA (λ) [Eq. (12)] and estimate of the contribution of fine and coarse aerosol in the spectral and integral AOD
Statistics of the parameters of Eq. (13)
Components of the total transparency and direct radiation in different areas (areas in the limits of the latitudinal zone are ordered from west to east)
