AERONET-A Federated Instrument Network and Data Archive for Aerosol Characterization

Sky measurements are performed at 440, 670, 870 and 1020 nm (Table 1). A single spectral measurement sequence (Langley sky) is made immediately after the Langley airmass direct sun measurement, 20 degrees from the sun. This is used to assess the stability of the Langley plot analysis according to O'Neill et al., 1984. Two basic sky observation sequences are made, the "almucantar" and "principal plane". The philosophy is to acquire aureole and sky radiances observations through a large range of scattering angles from the sun through a constant aerosol profile to retrieve size distribution, phase function and aerosol optical thickness (AOT). An almucantar is a series of measurements taken at the elevation angle of the sun for specified azimuth angles relative to the position of the sun. The range of scattering angles decrease as the solar zenith angle decreases thus almucantar sequences made at an optical airmass of 2 or more achieve scattering angles of 120 degrees or larger. Scattering angles of 120 degrees are typical of many sunsynchronous viewing satellites thus a measure of the satellite path radiance is approximated from the ground station. During an almucantar measurement, observations from a single channel are made in a sweep at a constant elevation angle across the solar disk and continues through 360 degrees of azimuth in about 40 seconds (Table 2). This is repeated for each channel to complete an almucantar sequence. More than four almucantar sequences are made daily at an optical airmass of 4, 3, 2 and 1.7 both morning and afternoon and, an almucantar is made hourly between 9 AM and 3 PM local solar time for the standard instrument and skipping only the noon almucantar for the polarization instrument. A direct sun observation is made during each spectral almucantar sequence.
Table 2. Almucantar and Principal Plane sequences for the standard and polarization instruments.

The standard principle plane sequence measures in much the same manner as the almucantar but in the principal plane of the sun where all angular distances from the sun are scattering angles regardless of solar zenith angle. This measurement sequence begins with a sun observation, moves 6 degrees below the solar disk then sweeps through the sun taking about 30 seconds for each of the four spectral bands.(Table 2). Principal plane observations are made hourly when the optical airmass is less than 2 to minimize the variations in radiance due to the change in optical airmass.
Polarization measurements of the sky at 870 nm are an option with this instrument. The sequence is made in the principal plane at 5 degree increments between zenith angles of -85 and +85 degrees. The configuration of the filter wheel requires that a near-IR polarization sheet is attached to the filter wheel. Three spectrally matched 870 nm filters are positioned in the filter wheel exactly 120 degrees apart. Each angular observation is a measurement of the three polarization filter positions. An observation takes approximately 5 seconds and the entire sequence about 3 minutes. This sequence occurs immediately after the standard principle plane measurement sequence.
Instrument Precision
We define the precision of the instrument as its ability to accurately reproduce results from multiple measurements under constant conditions using standardized techniques. Three methods will be used to assess the radiometric precision: (1) The variability of the digital numbers (DN) from the spectral response acquired from the two meter diameter integrating sphere at Goddard Space Flight Center which is used to determine the gain and offset calibrations of the sky radiance channels, (2) examination of dark current values taken during each sky radiance measurement and (3) the triplet variability of the DN's taken from Mauna Loa Observatory Langley observations was used to evaluate the sun channels.
All instruments are routinely calibrated with Goddard's two meter integrating sphere at least twice per year and the reference instruments approximately monthly. Each calibration session consists of three sequential measurements at four lamp levels (radiance levels). The sphere's precision is not well known however the absolute accuracy is ~5. % or less (Walker et al., 1991). Assuming the sphere has perfect precision we may use these data to estimate the precision of the sky channels. The percent deviation from the mean of each sequence was averaged from all the sequences since 1993 for each of the three reference instruments. In all but 1 case, the variability was much less than 1% of the mean value (Table 3A). Given these results, some of the variability in Table 3A could be attributed to the uncertainty in the precision of the integrating sphere and the potential for variability in the data collection procedure.
Over 3000 dark current values were examined for each instrument and the average values computed by wavelength for the sun and both sky (aureole- 2 to 6 degrees = sky¹ and dark sky 6 to 180 degrees=sky²) observations. The dark current values for the sun observations averaged less than 1 count compared to typical measurement values of 2000 to 15000 counts depending on wavelength, optical depth and airmass (Table 3B), thus for typical conditions the dark current is insignificant. The sky observations have a higher dark current value ranging from 2 to 14 counts with standard deviations of approximately the same magnitude. Typically this is about 1% of the signal and is subtracted prior radiance computation.
Table 3. The DNs were used to compute (A) the % variation from the mean for the sky channels, (B) the mean Dark current values for all measurement conditions and (C) the % variation of the mean triplet values during selected Mauna Loa Langley Plots for three field and reference instruments.

Langley plots from NOAA's Mauna Loa Observatory have been made to determine the spectral extraterrestrial voltage (V_o[lambda]) for these instruments since 1993. The observatory's high altitude and isolation from most local and regional sources of aerosols provides a very stable aerosol and irradiance regime in the mornings (Shaw, 1983). The Langley Plot is a log of the DN taken during these times plotted against the optical airmass between a range of 5 and 2. The intercept is the calibration coefficient and the slope the optical thickness. If the aerosol loading is constant, these points plot as a straight line. The deviation of these points from the linear regression line is a measure of the precision of the instrument although it does include atmospheric variation which we are assuming is negligible at Mauna Loa during the selected Langleys. Table 3C shows the average variability of a triplet is less than 1% and is most typically 0.3% for all three instruments. This is in agreement with the precision estimated from the integrating sphere analysis.
Instrument Calibration
Calibration refers to the determination of the calibration coefficients needed to convert the instrument output (DN) to a desired output, in this case aerosol optical thickness (AOT) and radiance (W/m2/sr/µm). The calibration accuracy is the level of accuracy with which a desired output is achieved using defined comparison procedures. Calibration is frequently traced back to the variability with which the calibration coefficients are determined to achieve that unit output. Thus instrument calibration is a combination of the instrument precision, the calibration procedure and the algorithms used. In this section, we will discuss the variability of the calibration coefficients we determine for the sky channels from the two meter integrating sphere, the spectral V_o from the Mauna Loa Langleys and the change in the calibration coefficients as a function of time. We will also discuss the intercomparison procedure for transferring the V_o calibration coefficients from a reference instrument to a field instrument and the computation of the resultant variability.
The sphere calibration procedure given in the previous section allows us to compute a gain and offset for each sky wavelength. The mean dark current DN is typically between 0 and 14 counts (the median DN is zero to one for the sun channels) (Table 3b) which is subtracted from the DN thus giving an offset of zero. The Instrument DNs are plotted against the exitant radiance from the integrating sphere and a gain is computed from the linear regression fit through the origin. The mean gain is computed from three regression gains made for each session. The accuracy of the sphere is reported as ±5% (Walker et al., 1991) thus the calibration coefficient accuracy can be no better than 5% plus the variability of the three regressions (precision) or conservatively ±~ 5.5%. (Unpublished studies of the two meter integrating sphere in 1997 indicate the absolute accuracy is between 1 and 3% depending on wavelength.)
The V_o calibration coefficients are typically computed from an average of five or more Langley plots obtained at the Mauna Loa Observatory. The variability of the retrieved mean V_o as measured by the coefficient of variation (CV, standard deviation/mean) indicates the combined uncertainty of the atmosphere, instrument and the repeatability of the calibration procedure. The averaged Mauna Loa Langleys V_o obtained during all calibration sessions have a CV of ~0.25 to 0.50% for the visible and near-IR wavelengths, ~0.5 to 2% for the UV to ~1 to 3% for the water vapor channel (Table 4 and continuing observations).
The Mauna Loa (MLO) calibration is conducted with two simultaneously operating reference instruments. Comparisons are made between ratios of raw spectral voltages as a check for instrument repeatability. A diurnal variation of less than 1% of the ratioed voltages is considered acceptable. Approximately monthly the MLO master instruments are swapped with two reference instruments located at GSFC. The GSFC reference instruments are used for intercomparison with field instruments. Monitoring voltage ratios is continued for all master instruments and field instruments during the calibration procedure.
Table 4, The mean CV in percent by wavelength (nm) of the Mauna Loa derived Langley V_o for all of the wavelengths used in the reference CIMEL sun photometers.

With respect to the long term stability of the calibration coefficients, the optical interference filters are the limiting factors. Periodic sphere gains and mountain top Langley calibration coefficients have been determined since 1993. The results are typical for interference filters. On average, there has been a decrease from 1 to 5% per year and, after 2 years, there has been a rapid decay in some filters (Table 5). However, starting in 1997 we installed ion assisted deposition (IAD) iinterference filters in all instruments with the expectation of improved filter stability with time, which in fact is noted in Table 5 for instrument #11. Since the % decrease in the time dependent calibration coefficients is usually greater than the uncertainty of a semiannual V_o determination we use a linear interpolation of the V_o between calibration dates. This requires that the instrument calibration coefficient be followed closely. Thus, until more information is available, we calibrate instruments on a 6 month rotation and change filters after two years of field use. Therefore the percentage changes which occur between V_o calibrations are actually a factor of 2 to 3 smaller than shown in Table 5 since these values are on a % change per year.
Most instruments cannot be calibrated at Mauna Loa and a well calibrated integrating sphere with sufficient radiometric output is not common, therefore most instruments are calibrated at Goddard Space Flight Center with the two meter integrating sphere and intercomparisons against the Goddard reference instrument with a Mauna Loa derived V_o. Intercomparisons are made by solving Eq. 1 for the field instrument V_o based on the reference instrument [tau]_a during simultaneous observations (time difference of less than 5 seconds), under clear stable atmospheric conditions ([tau]_a440 less than 0.15). The CV of the V_o computed from these comparisons is typically larger than the reference instrument uncertainty. The total error is the uncertainty attributed to the field instrument calibration coefficient due to transfer of calibration from the reference instrument plus the error from the reference instrument defined from the Mauna Loa calibration. As with the reference instruments, calibration coefficients are then linearly interpolated between the calibration tie points unless independent information suggests a different method as in the case of a change in filters at which time new calibration comparisons must be made. The spectral voltage ratios of the field instrument are compared to the reference instruments during several days. Variations throughout a large range of optical airmass (typically 1.5 - 6) of less than ±1% are considered acceptable.
Table 5, The decay rate of zero airmass voltages, V_o, (%/yr) is shown for filters less than two years old for each reference instrument.

Measurements of the spectral temperature sensitivity of the instrument in a temperature controlled chamber showed agreement with the manufacturers published temperature sensitivity of the detectors. To date, only the 1020 nm channels showed significant temperature variation (0.25%/^oC ±0.05%/^oC ) warranting a correction to a reference temperature in the processing. However, for polarization instruments, measurements indicate that the plastic polarizing filter introduces a temperature sensitivity of ~0.20%/^oC to the polarized 870 nm radiance measurements.
Data Accuracy
Various instrumental, calibrational, atmospheric and methodological factors that influence the precision and accuracy of optical depth determination have been pointed out clearly in a series of publications (Shaw, 1976; Reagan et al., 1987 and Russel et al., 1993) and attempts to account for or minimize these are described in previous sections. Instrument uncertainty due to electro-optical precision is for all practical purposes insignificant (Table 3) for a properly operating instrument. The variability of the atmosphere is characterized by the variability of the triplet optical thicknesses which may at times be cloud contaminated. This uncertainty is computed, can be used as a screening tool, and may be retrieved from the AERONET data base. Additionally the uncertainty due to calibration is tracked with all time dependent data and may also be retrieved from the data base. Typically the total uncertainty in AOT from a newly calibrated field instrument under cloud free conditions is <±0.01 for [lambda] >440 nm and <±0.02 for shorter wavelengths. Uncertainty in the water vapor retrieval is limited by larger uncertainty in the Vo for the 940 nm channel and by the uncertainty of the radiosonde intercomparisons, typically less than 12%.
The uncertainty of the sky radiance data is more difficult to ascertain since these only constitute single observations and no absolute self-calibration procedure is implemented between the sphere calibrations. Based on the sphere calibration, the uncertainty in the sky radiance at the time of calibration is assumed <±5% for all four channels at the time of calibration. Scattering aerosol optical depth is directly related to the aureole brightness and thus the accuracy is a function of the sky calibration. We feel that for low optical depth monitoring the sky brightness may retrieve scattering optical depths with less absolute error than traditional extinction approaches (Table 6) assuming perfect straylight rejection and a uniformly distributed aerosol in the aureole. Development of an in situ sky calibration procedure is under evaluation, (Nakajima et al., 1996).
Table 6. The absolute value (and % error) of the extinction optical depth and scattering optical depth at airmass of 2 clearly illustrate the possible advantages of using the scattering optical depth for low optical depth ranges.

Data Transmission
Data are transmitted from the memory of the sun photometer via the Data Collection Systems (DCS) to either of geosynchronus satellites GOES-E, GOES-W, or METEOSAT (GMS is anticipated in 1998) and then retransmitted to the appropriate ground receiving station. The data can be retrieved for processing either by modem or internet linkage resulting in near real-time acquisition from almost any site on the globe excluding poleward of 80° latitude. The DCS is a governmental system operated for the purpose of transmitting low volume environmental data from remote sites for various institutions and government agencies.
Each station on the GOES and METEOSAT networks has been assigned a user ID and transmission time window passing up to 30 kbytes per day in 24 and 48 individual transmissions at hourly and half-hourly intervals respectively. During each transmission, a packet of data and status information are time stamped by the radiometer, the transmitter and the central receiving station (Wallops Island, VA, USA for GOES; Darmstadt, Germany for METEOSAT; and Tokyo, Japan for GMS). Typically the data are maintained in the receiving station computers for 3 to 5 days before they are overwritten. The data are retrieved daily from the central receiving station which we term near real-time.
Processing System
A fundamental component of the AERONET system is a package of user friendly UNIX software that provides near real-time information on the status and calibration of the instruments, provides data processing with referenced and generally accepted processing algorithms, provides an orderly archive of the data and provides convenient electronic access for all users to the raw and processed data base. We shall discuss these aspects of the current operational state of the software and future enhancements.
Instrument and Network Status
The radiometer data stream includes date, time, temperature, battery voltage, wet sensor status and time of transmission as well as several levels of identification numbers. The DCP adds a time stamp at the time of transmission as does the DCS receiving station plus checks for parity errors and signal strength of the transmission. After data are downloaded from the central receiving station, a status report and a trouble shooting report are automatically generated and e-mailed to appropriate system and instrument managers and an internet homepage provides these information to the entire community. The status report provides a comprehensive assessment of the operation of the radiometer and DCP for the data transmitted with the current download. Network managers then have sufficient information to assess the operation of individual stations. To more quickly identify trouble spots, a troubleshooting report is generated that lists by instrument only information that fails to meet normal operating thresholds i.e. low battery voltage, transmission time error, missed transmission etc. This approach can identify remote station problems quickly often leading to same day resolution. Documentation of the status report is available under the AERONET home page http://spamer.gsfc.nasa.gov.
Data Processing
There is lack of agreement on corrections, calibration procedures, data analysis procedures etc. often caused by divergent error tolerances or specific requirements of various investigators. We have implemented a series of processing algorithms on a UNIX server that have been published in the open literature and/or are generally accepted by the scientific community (Table 7). These algorithms impose a processing standardization on all of the data taken in the network facilitating comparison of spatial and temporal data between instruments. The archival system allows the user community to access either the raw or processed data via internet for examination, analysis and/or reprocessing as needed. The archival browse algorithms are collectively known under the program name "demonstrat" which graphically provides access to all aspects of the data base and through the AERONET homepage (http:/spamer.gsfc.nasa.gov). The program operates on a workstation called "spamer.gsfc.nasa.gov". The algorithms within "demonstrat" comprise three principal categories; time dependent retrievals such as AOT and Pw, calibration assessment, and sky radiance retrievals. There are a growing number of sub processing algorithms within each of these. As importantly, `demonstrat' allows all data to be retrieved through "FTP" and e-mail access for personal computer analysis and/or reprocessing as the user requires. As new and improved approaches and models are accepted within the community the processing may be applied uniformly to the network wide data base. Additionally access to the data base through demonstrat provides an opportunity for testing new algorithms and models for an increasingly diverse set of measurements for a variety of locations and conditions. The following figures were obtained directly from the `demonstrat' output to illustrate the access to the data base.
Table 7, the algorithms, inputs, corrections and models used in computing the aerosol optical thickness, Pw, spectral irradiance, and sky radiance inversions are referenced.

Archival Browser (`demonstrat')
The custom browser `demonstrat' allows a comprehensive method of viewing and screening the data in either raw or processed form. Following are a few of the options available in demonstrat that we feel are important for use in a network data base.
Time Dependent AOT Retrievals. The time dependence window serves as the access point for all other windows. The aerosol optical thickness, precipitable water, wavelength exponent and calibration coefficient trends as well as the status indicators (battery voltage, temperature and wet sensor) may be plotted as a function of time in this window. For a particular instrument and location, all or part of the data may be displayed by interactive cursor subsetting. For example, the dry season data (June to October) from Cuiaba, Brazil (Holben et al., 1996) clearly shows the increase in aerosol optical thickness as the burning season begins in August (Figure 1). Subsetting to eight days of data or less, the UTC time scale and a local time bar are drawn, the mean 15 minute. direct sun AOT observations are plotted and almucantar (triangles) principle plane (squares) and successful inversions (o and x) are shown under the time scale (Figure 2). A hatched line above the time scale indicates Langley data and vertical bars inside the plot indicate that the wet sensor has been activated and no sun data are available. Individual points may be rejected in these windows.

Figure 1, The aerosol optical thickness dry season record for Cuiaba, Brazil showing a large increase in August and September 1993 due to region wide burning.


Figure 2, The aerosol optical thickness in Cuiaba on August 14, 1993 (top) shows significant aerosol loading in contrast to June 23 (bottom). Note the addition of time dependent information on the abscissa including almucantar ([Delta]),principal plane([]), inversion (o or x) and Langley data (|).
Calibration Assessment. Historically, uncertainty due to calibration of sun photometers has limited their wide scale deployment and long term use. No new methods are offered however "demonstrat" imposes a standard computation of aerosol optical thickness and Pw calibration coefficients and in so doing renders a simple method via a graphics window for the user to assess the quality of these calibration coefficients interactively from the on-line data base. Two windows were implemented for standardizing the direct sun calibration coefficient procedure and assessing their quality control. The first is the traditional Langley Plot with the modified Langley method used for water vapor retrieval. A second method is a simple intercomparison.
The radiometer acquires a Langley data sequence each morning and afternoon between an optical airmass of 2 and 7. The interactive calibration routine allows manual rejection of data points and automatically computes a table of Vo's for each wavelength. Tabled Vo's are recomputed and displayed after each rejection. The Vo's may be applied to the original Langley data and aerosol optical thickness plotted as a function of time or airmass in two additional windows for further inspection of the quality of the Langley Plot. The water vapor calibration coefficient determined by the modified Langley method (Bruegge et al., 1992 and Reagan et al., 1992) is performed in much the same way. The water vapor transmittance is modeled from each 940 nm filter function using MODTRAN and has been shown to be largely independent of temperature and water vapor profiles (Halthore et al., 1996). Both Langley methods are typically used only for absolute calibration analysis with more restrictive airmass ranges from high mountain top acquisitions for our reference instruments. This is particularly important for the UV and 940 nm (water vapor) wavelengths.
An intercomparison algorithm searches a specified portion of the data base for space and time coincidence (Fig. 3) of two instruments. Sun data are automatically intercompared by spectral aerosol optical thickness. A table of old and new calibration coefficients is generated from which an assessment for further calibration is made.
The history of the calibration coefficient determinations for each instrument is easily tracked on demand by a calibration tree showing the date, location and reference instrument from which each intercomparison was made, back to a mountain top Langley or sphere calibration. Additionally a time dependent plot of the calibration coefficients shows the trends over time for the instrument in question.
...
Fig. 3 shows the intercomparison window which allows recomputation of Vo values from a time series of AOTs of two simultaneously measuring instruments. Voltages from a reference instrument (top plot) are ratioed with voltages from a field instrument (bottom plot) resulting in a table of old and new V_os. Options to examine time dependent voltage ratios may also be accessed from this window.
Sky Radiance Inversions. The almucantar window displays the four channel sky radiances as a function of scattering angle, volume size distribution from 0.1 to ~8. µm, scattering phase function and a table of the aerosol optical thickness and wavelength exponent computed from both direct sun and the aureole measurements (Fig 4). Additionally the spectral asymmetry factor is computed from the phase function. From the radiance data, a window may be opened with zoom capabilities which separates the four spectral sky radiance bands into single color coded bands allowing close inspection of the data. The program automatically checks the quality of the almucantar data by examining the symmetry of the aureole radiances about the sun. If the angular asymmetry defined as |(l-r)/(l+r)*0.5| where l=left side and r=right side radiance pairs, exceeds 10%, those pairs are removed from the inversion process. If the standard deviation of the difference between aureole pairs divided by the averaged value of the angular pairs exceeds 10% or there are not a sufficient number of data points remaining with symmetry (10), the data are not inverted. The inversion routine used is that of Nakajima et al., (1983) and has a number of options that will be implemented over time. This will include size distribution inversions by combining the spectral optical thickness from direct sun measurements and aureole data In cases where the almucantar or principle plane data are not available, an interactive inversion from the spectral AOT data can be made but the retrieved size range will be smaller due to reduced sensitivity to large particles.
The principle plane data are processed using the same inversion; however only data on the zenith side from the solar disc are used in the inversion due to asymmetry induced by the ground reflectance and an increasingly large optical airmass. The principle plane window has identical capabilities as the almucantar window. The test for the quality of the data is simply the smoothness of the curve.
(a)
(b)
Figure 4 A successful inversion of almucantar radiances during low aerosol loading (4a) and high aerosol loading (4b) is possible when the radiance data are symmetric about the sun (upper left plot within window). Inversions produce a volume size distribution with good accuracy from 0.1 µm to about 8 µm aerosol radii (lower left window). The aerosol optical thickness and wavelength exponent are computed (upper right window) and compared to that measured by direct sun observation. The spectral phase function and asymmetry factor (lower right side of window) from the aureole inversion are also computed using Nakajima et al.'s (1996) `pakrad' code.
Radiative Transfer Model Interface. We have incorporated a parameterized spectral cloud free flux model SPECTRAL2 (Bird and Riordan, 1986) to compute the total, direct and diffuse down welling flux in the total solar spectrum and photosynthetically active radiation (PAR) bands from the measured aerosol and water vapor measurements. Single scattering albedo is the only required parameter which the instrument does not measure and thus must be supplied by the user. The interactive computations are made for any instantaneous or time dependent measurements. The window displays the spectral flux curves for the total, direct and diffuse irradiance and a summary box gives integrated values for each component of the broad band (0.3-4.0µm) and PAR (0.4-0.7 µm). The model is applied to the time dependence creating a data set of integrated fluxes. Options exist to compute coincident fluxes for user specified background conditions. Ratios of ambient vs. background conditions are computed and displayed in a summary box.
An interface to the more rigorous 6S model has been developed. The size distribution parameters ( ) deduced from the almucantar inversion as well as the index of refraction (imaginary and real) can easily be input to the 6S model (Vermote et al., 1996, 1997) and used to compute the phase function, extinction and scattering coefficient at any wavelength between 0.25 and 4.0µm. These quantities are then used to generate a large set of atmospheric parameters in addition to the simulation of the signal observed from aircraft or space by a variety of sensors. The computation of the phase function and extinction is done by the MIE subroutine (described in details in Vermote et al., 1996). Computations are restricted to the case of the scattering of electromagnetic waves by a mixture of homogeneous isotropic spheres, the physical properties of particles whose sizes are comparable to or larger than the wavelength. These assumptions are in accordance with those used in the sun photometer size distribution retrieval algorithm.
Cloud Screening. Data are taken by the automatic instruments under all non precipitation conditions causing significant cloud contamination in some of the raw data. Two approaches are used. The cloud contaminated data base available through domonstrat provides for the user simple cloud screening tools based on the variability of the triplets and for continental non dust aerosols the spectral dependence of the AOT. Despite these screenings, some cloud contaminated data will be displayed and further screening is left to the user. A second data base has been generated based on a series of triplet variability, time dependent tests and thresholds to automatically screen the data base and provide a basic quality control of the data base (Smirnov, 1998).
Automatic cloud screening of the almucantar and principal plane data are by symmetry and smoothness checks respectively of the data about the solar disc as explained under `sky radiance inversions'.
Downloading Data. Labeled spreadsheet export files may be created during a `demonstrat' browser session of all raw or processed data in the data base and all data processed during a session e.g. modeled fluxes. Data for export may be selected by location, time, and the type of raw or processed data desired. The data may be downloaded to any computer with internet access through the AERONET home page, using a guest account or may be e-mailed directly during a "demonstrat session". Homepage data access is under development.
The public domain data base has developed as an honor system among the numerous contributing PI's according to the following requirement: Analysis and publication of any part of the data base by non PIs requires permission of the owner. We recognize that this tennant is the key to expanding the AERONET data base and expect the scientific community to honor it. The owner is identified when the data are retrieved through the homepage or demonstrat.
Global Perspective
Through 1997 approximately 100 instruments have been included in the network and 60 instruments were deployed world wide on various Islands, North America, South America, Europe, Africa, and the Middle East, fostered by collaboration between international, national, and local agencies, private foundations and individuals (Fig. 5). As the data base continues to expand, the processing system becomes more sophisticated and more users have access to the data base, the need to provide better access to and quality assurance of the data base becomes more critical. To aid in that effort, the reference data base is located on 'spamer.gsfc.nasa.gov' at Goddard Space flight Center in Greenbelt, MD, USA or `loaser.univ-lille1.fr' (IP number is 134.206.50.10) at Lab. d'Optique Atmosphérique, U.S.T. de Lille, 59655-Villeneuve d'Ascq,France for European access. A third supported data base will be established in Tokyo, Japan to support access to the data from eastern Asia. Identical clones of these systems have been established at various locations to facilitate access to the data for local activities. All processing changes are made to the entire spamer reference data base to maintain uniform processing.
An automatic, computerized quality assured data base is available and is continuing to be improved providing a screened data set to the scientific community. It is accessed by a simplified version of the `demonstrat' browser, `demonstrat II', available through the AERONET homepage. The data must exceed specified optical, radiometric and calibrational specifications as well as incorporating screening algorithms for cloud contamination that are functionally related to temporal and spectral behavior of the aerosol optical depth. Further details will be included in the homepage.
The network is expected to provide characterization of aerosol optical properties, a data base for atmospheric correction, validation of satellite based aerosol retrievals, and satellite observations of ocean color. The simple technology and international collaboration that has produced AERONET can be expanded to complimentary data sets of BRDF, automatic lidar systems, and radiation networks.

Figure 5, The approximate location of instruments is represented by the colored circles. Measurements are made at permanent sites year round. Data are taken seasonally at high latitudes and/or when cloud cover permits. In 1997 nearly 60 locations contributed to the data base.
Conclusion
We believe that a successful system for long term monitoring and characterization of aerosols requires automatic low maintenance radiometers, real time data reception and processing as well as an easily accessible data base for the scientific community. We have combined commercially available hardware, international agency collaborations, a public domain software and a collaborative philosophy among investigators to form a network that has yielded regionally based aerosol amounts and properties in North and South America, Africa, the Middle East and various Atlantic and Pacific islands. More systems will come on-line in the years ahead that will provide greater spatial coverage and synergism between and satellite measurements to achieve the objectives of specific intensive field campaigns and global climate change assessment. The philosophy of an open interactive data base is expected to promote research and collaboration among investigators.
Acknowledgment--The authors wish to thank Diane Wickland and Tony Janetos of NASA Headquarters for providing the initial support for this project, Michael King of NASA's EOS Project Science Office for continued support, Chris Justice for contributing to the vision of the network, John Vande Castle and Gunar Fedosejevs for actively participating in development of the network. Many thanks to Bruce Forgan for his detailed constructive recommendations to this manuscript and the other anonymous reviewers for their useful comments. Numerous others have contributed significant time, resources and funds to this effort, our thanks to them.
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