<dataset xmlns="http://datafed.net/xs/Catalog">
    <data>
        <data_domain>
            <data_domain_abbr>Aerosol</data_domain_abbr>
            <data_domain_name>Aerosol</data_domain_name>
            <data_domain_desc>
            </data_domain_desc>
        </data_domain>
        <dataset_doc>
            <dataset_abbr>AERONET_H</dataset_abbr>
            <dataset_name>AERONET_H</dataset_name>
            <dataset_desc>AERONET_H, A globally distributed network of spectral aerosol optical depth (AOD), inversion products, and precipitable water in diverse aerosol regimes, continuously, over long term.</dataset_desc>
            <dataset_access_url>http://aeronet.gsfc.nasa.gov/new_web/data.html</dataset_access_url>
            <citation_url>http://aeronet.gsfc.nasa.gov/new_web/data_usage.html</citation_url>
            <icon_small>http://datafed.net/Datasets/Icons/AERONET_HIcon50.gif</icon_small>
            <icon_big>http://webapps.datafed.net/icon.wsfl?width=100&amp;height=100&amp;draw=text&amp;value=AERO NET&amp;font_size=10</icon_big>
        </dataset_doc>
        <provider>
            <provider_abbr>NASA</provider_abbr>
            <provider_name>NASA Atmospheric Data Center</provider_name>
            <provider_desc>
            </provider_desc>
            <provider_url>http://www.nasa.gov/</provider_url>
            <provider_icon_url>http://www.datafed.net/icons/NASAIcon50.gif</provider_icon_url>
        </provider>
        <sample_platform>
            <sample_platform_abbr>Network</sample_platform_abbr>
            <sample_platform_name>Monitoring Network</sample_platform_name>
            <sample_platform_desc>
            </sample_platform_desc>
        </sample_platform>
        <sample_method>
            <sample_method_abbr>Point</sample_method_abbr>
            <sample_method_name>Point Sample</sample_method_name>
            <sample_method_desc>
            </sample_method_desc>
        </sample_method>
    </data>
    <PointParamLocTime>
        <dimensions>
            <parameter_dim dim_type="parameter">
                <default_cursor>
param_abbr,param_code,param_name,param_unit,scale_min,scale_max,vertical,geoss
"AOT_1640","AOT_1640","AOT_1640","unknown",0,1,"Surface","true"
</default_cursor>
                <granules>
param_abbr,param_name,param_unit,scale_min,scale_max,vertical,geoss
"Angstrom_440_870","440-870 Angstrom","unknown",0,1,"Surface",""
"Angstrom_380_500","380-500 Angstrom","unknown",0,1,"Surface",""
"Angstrom_440_675","440-675 Angstrom","unknown",0,1,"Surface",""
"Angstrom_500_870","500-870 Angstrom","unknown",0,1,"Surface",""
"Angstrom_340_440","340-440 Angstrom","unknown",0,1,"Surface",""
"Angstrom_440_675_Polar","440-675Angstrom(Polar)","unknown",0,100,"Surface",""
"AOT_1640","AOT_1640","unknown",0,1,"Surface",""
"AOT_1020","AOT_1020","unknown",0,1,"Surface",""
"AOT_870","AOT_870","unknown",0,1,"Surface",""
"AOT_675","AOT_675","unknown",0,1,"Surface",""
"AOT_667","AOT_667","unknown",0,1,"Surface",""
"AOT_555","AOT_555","unknown",0,1,"Surface",""
"AOT_551","AOT_551","unknown",0,1,"Surface",""
"AOT_532","AOT_532","unknown",0,1,"Surface",""
"AOT_500","AOT_500","unknown",0,1,"Surface",""
"AOT_490","AOT_490","unknown",0,1,"Surface",""
"AOT_443","AOT_443","unknown",0,1,"Surface",""
"AOT_440","AOT_440","unknown",0,1,"Surface",""
"AOT_412","AOT_412","unknown",0,1,"Surface",""
"AOT_380","AOT_380","unknown",0,1,"Surface",""
"AOT_340","AOT_340","unknown",0,1,"Surface",""
"Water","Water","cm",0,1,"Surface",""
"TripletVar_1640","%TripletVar 1640","unknown",0,1,"Surface",""
"TripletVar_1020","%TripletVar 1020","unknown",0,1,"Surface",""
"TripletVar_870","%TripletVar 870","unknown",0,1,"Surface",""
"TripletVar_675","%TripletVar 675","unknown",0,1,"Surface",""
"TripletVar_667","%TripletVar 667","unknown",0,1,"Surface",""
"TripletVar_555","%TripletVar 555","unknown",0,1,"Surface",""
"TripletVar_551","%TripletVar 551","unknown",0,1,"Surface",""
"TripletVar_532","%TripletVar 532","unknown",0,1,"Surface",""
"TripletVar_500","%TripletVar 500","unknown",0,1,"Surface",""
"TripletVar_490","%TripletVar 490","unknown",0,1,"Surface",""
"TripletVar_443","%TripletVar 443","unknown",0,1,"Surface",""
"TripletVar_440","%TripletVar 440","unknown",0,1,"Surface",""
"TripletVar_412","%TripletVar 412","unknown",0,1,"Surface",""
"TripletVar_380","%TripletVar 380","unknown",0,1,"Surface",""
"TripletVar_340","%TripletVar 340","unknown",0,1,"Surface",""
</granules>
            </parameter_dim>
            <location_dim dim_type="location">
                <default_cursor>
loc_code,lat,lon,elev
"Abracos_Hill",-10.76,-62.3580,200.0
</default_cursor>
                <granules>
loc_code,lat,lon,elev
"Abracos_Hill",-10.76,-62.3580,200.0
"Abu_Al_Bukhoosh",25.4950,53.146,24.0
"Abu_Dhabi",24.476,54.3290,7.0
"Adelaide_Site_7",-34.7250,138.656,30.0
"Agoufou",15.345,-1.479,305.0
"Aguas_Emendadas",-15.582,-47.6560,1100.0
"Ahi_De_Cara",37.1170,-3.23,2103.0
"Aire_Adour",43.7000,0.25,80.0
"Al_Ain",24.2420,55.7050,283.0
"Al_Dhafra",24.254,54.5500,40.0
"Al_Khaznah",24.159,55.1010,192.0
"Al_Qlaa",24.1330,53.0330,5.0
"Albany_Oregon",44.583,-123.067,67.0
"Alta_Floresta",-9.871,-56.104,277.0
"Ames",42.021,-93.7750,338.0
"Amsterdam_Island",-37.8100,77.5730,30.0
"Andenes",69.278,16.0090,379.0
"Andros_Island",24.7000,-77.8000,0.0
"Angiola",35.9470,-119.538,210.0
"Anmyon",36.5390,126.330,47.0
"Appledore_Island",42.987,-70.6150,35.0
"Arica",-18.472,-70.3130,25.0
"Ariquiums",-9.917,-63.0330,80.0
"Armilla",37.1330,-3.242,691.0
"Ascension_Island",-7.976,-14.415,30.0
"ATHENS-NOA",37.9880,23.775,130.0
"Autilla",41.9970,-4.603,873.0
"Avignon",43.9330,4.878,32.0
"Azores",38.5300,-28.6300,50.0
"Bac_Giang",21.291,106.225,15.0
"Bac_Lieu",9.28,105.730,10.0
"BackGarden_GZ",23.296,113.021,150.0
"Bahrain",26.208,50.6090,25.0
"Balbina",-1.917,-59.487,80.0
"Banizoumbou",13.541,2.665,250.0
"Barbados",13.15,-59.6170,114.0
"Barcelona",41.3860,2.117,125.0
"Bareilly",28.3900,79.4370,169.0
"Barrow",71.3120,-156.665,0.0
"Beijing",39.9770,116.381,92.0
"Belsk",51.8370,20.792,190.0
"Belterra",-2.648,-54.952,70.0
"Bermuda",32.3700,-64.6960,10.0
"Bethlehem",-28.2480,28.333,1709.0
"Biarritz",43.4830,-1.55,0.0
"Bidi_Bahn",14.06,-2.45,0.0
"Big_Meadows",38.5220,-78.4360,1082.0
"Billerica",42.528,-71.2690,82.0
"Birdsville",-25.899,139.346,46.0
"Black_Forest_AMF",48.5400,8.397,511.0
"Blida",36.5080,2.881,230.0
"Bodele",16.8830,18.5500,179.0
"Bonanza_Creek",64.7430,-148.316,150.0
"Bondoukoui",11.85,-3.75,0.0
"BONDVILLE",40.0530,-88.3720,212.0
"BORDEAUX",44.7880,-0.579,40.0
"Bordman",45.8170,-119.667,200.0
"Boulder",40.0170,-105.25,1600.0
"Bozeman",45.666,-111.046,1530.0
"Bragansa",-0.834,-46.6410,55.0
"Brasilia",-15.917,-47.9000,1100.0
"Bratts_Lake",50.2800,-104.700,586.0
"Brookhaven",40.8700,-72.889,33.0
"Brussels",50.7830,4.35,120.0
"BSRN_BAO_Boulder",40.0450,-105.006,1604.0
"Bucarest",44.4500,26.525,44.0
"Bucharest_Inoe",44.348,26.0300,93.0
"Burjassot",39.5080,-0.418,30.0
"Burtonsville",39.0940,-76.9500,140.0
"Bushland",35.187,-102.094,1168.0
"Cabauw",51.9710,4.927,-1.0
"Cabo_da_Roca",38.7830,-9.5,140.0
"Cabo_Raso",38.709,-9.486,20.0
"Caceres",39.479,-6.343,397.0
"Cairo_EMA",30.0810,31.2900,70.0
"Cairo_University",30.0260,31.2070,50.0
"Calipso_Ridgely",38.9490,-75.8820,15.0
"Calipso_West_Denton",38.9150,-75.8940,15.0
"Calipso_Zion",39.9320,-76.1990,120.0
"Campo_Grande",-20.4500,-54.6170,500.0
"Campo_Grande_SONDA",-20.438,-54.5380,677.0
"Canberra",-35.271,149.111,600.0
"CANDLE_LAKE",53.7330,-105.267,503.0
"Cape_San_Juan",18.3840,-65.6200,15.0
"Capo_Verde",16.733,-22.9350,60.0
"Carlsbad",32.3690,-104.233,942.0
"Carpentras",44.083,5.058,100.0
"CART_SITE",36.6070,-97.486,318.0
"CARTEL",45.3790,-71.931,300.0
"Cartel_X",45.3790,-71.931,300.0
"CCNY",40.8210,-73.9490,100.0
"CEILAP-BA",-34.5670,-58.5,10.0
"CEILAP-RG",-51.6000,-69.32,15.0
"CEILAP-UTN",-34.66,-58.4690,27.0
"Chao_Jou",22.513,120.529,0.0
"Chapais",49.8220,-74.9750,373.0
"Chebogue_Point",43.7470,-66.1230,0.0
"Chen-Kung_Univ",23.0,120.217,50.0
"Chequamegon",45.9330,-90.25,0.0
"Cheritan",37.2890,-75.972,5.0
"Chiang_Mai",18.813,98.987,324.0
"Chiang_Mai_Met_Sta",18.771,98.972,312.0
"Chilbolton",51.1440,-1.437,88.0
"China_Lake",35.674,-117.745,800.0
"Chinhae",35.1560,128.652,69.0
"Chulalongkorn",13.736,100.530,115.0
"Churchill",58.736,-93.8180,10.0
"City_GZ",23.0810,113.158,58.0
"Clermont_Ferrand",45.7600,2.962,1464.0
"Coconut_Island",21.4330,-157.790,0.0
"Coleambally",-34.8100,146.064,127.0
"Columbia_SC",34.0230,-81.0360,104.0
"Concepcion",-16.138,-62.028,500.0
"Corcoran",36.1030,-119.566,110.0
"Cordoba-CETT",-31.524,-64.4640,730.0
"COVE",36.9000,-75.7100,37.0
"COVE_SEAPRISM",36.9000,-75.7100,24.0
"Creteil",48.7880,2.443,57.0
"Crozet_Island",-46.4350,51.8500,221.0
"CRPSM_Malindi",-2.996,40.194,12.0
"CRYSTAL_FACE",25.65,-80.4220,5.0
"Cuiaba",-15.5,-56.0,250.0
"CUIABA-MIRANDA",-15.729,-56.021,210.0
"Dahkla",23.7170,-15.95,12.0
"Dakar",14.394,-16.959,0.0
"Dalanzadgad",43.577,104.419,1470.0
"Dalma",24.5020,52.3320,0.0
"Darwin",-12.424,130.892,29.0
"Davos",46.813,9.844,1596.0
"Dead_Sea",31.1,35.4500,-410.0
"Dhabi",24.4810,54.3830,15.0
"Dhadnah",25.513,56.3250,81.0
"Dharwar",15.429,74.9890,700.0
"Djougou",9.76,1.599,400.0
"DMN_Maine_Soroa",13.217,12.023,350.0
"Dongsha_Island",20.6990,116.729,5.0
"Dry_Tortugas",24.628,-82.8720,0.0
"Dunedin",-45.8640,170.514,43.0
"Dunhuang",40.0380,94.7940,1300.0
"Dunkerque",51.035,2.368,0.0
"Egbert",44.2260,-79.75,264.0
"Egbert_X",44.2260,-79.75,264.0
"Eilat",29.503,34.917,15.0
"EIM-Sindos",40.6900,22.8000,12.0
"El_Arenosillo",37.105,-6.733,0.0
"El_Refugio",-14.766,-62.035,225.0
"EOPACE1",36.1820,-75.7510,0.0
"EOPACE2",36.1840,-75.7450,0.0
"EPA-NCU",24.968,121.185,144.0
"Epanomi",40.375,22.9780,20.0
"Ersa",43.0040,9.359,80.0
"ETNA",37.6140,15.019,736.0
"Etosha_Pan",-19.1750,15.914,1131.0
"EVK2-CNR",27.959,86.8130,5050.0
"Evora",38.5680,-7.912,293.0
"FLIN_FLON",54.6700,-101.690,305.0
"Fontainebleau",48.4070,2.68,85.0
"Fort_McMurray",56.7520,-111.476,0.0
"FORTH_CRETE",35.333,25.282,20.0
"Frenchman_Flat",36.8090,-115.935,940.0
"Fresno",36.7820,-119.773,0.0
"Fresno_X",36.7820,-119.773,0.0
"Gaithersburg",39.1330,-77.208,50.0
"Gandhi_College",25.871,84.1280,60.0
"Gerlitzen",46.6780,13.907,1900.0
"GISS",40.798,-73.9600,50.0
"GOA_INDIA",15.453,73.806,20.0
"Gosan_SNU",33.292,126.162,72.0
"Gotland",57.917,18.9500,10.0
"Granada",37.1640,-3.605,680.0
"GSFC",38.9920,-76.8400,87.0
"Guadeloup",16.333,-61.5,0.0
"Guam",13.431,144.801,62.0
"Gustav_Dalen_Tower",58.5940,17.4670,25.0
"Gwangju_K-JIST",35.2280,126.843,52.0
"Hagerstown",39.708,-77.7250,200.0
"Halifax",44.638,-63.5940,65.0
"Hamburg",53.5680,9.973,105.0
"Hamim",22.9670,54.3000,209.0
"Hampton_Roads",36.7830,-76.4500,10.0
"Hangzhou-ZFU",30.257,119.727,14.0
"Harvard_Forest",42.5320,-72.1880,322.0
"Hefei",31.9050,117.162,36.0
"Helgoland",54.1780,7.887,33.0
"Helsinki",60.2040,24.961,52.0
"Helsinki_Lighthouse",59.9490,24.9260,20.0
"Hermosillo",29.0750,-110.960,237.0
"Hetauda",27.4280,85.0310,465.0
"HJAndrews",44.2390,-122.224,830.0
"Hog_Island",37.4200,-75.7000,50.0
"Hong_Kong_Hok_Tsui",22.2100,114.258,80.0
"Hong_Kong_PolyU",22.3030,114.18,30.0
"Hornsund",77.0,15.55,0.0
"Howland",45.2000,-68.7330,100.0
"Hua_Hin",12.634,99.9510,1.0
"Hyytiala",61.8460,24.296,191.0
"ICIPE-Mbita",-0.417,34.2000,1125.0
"IER_Cinzana",13.278,-5.934,285.0
"IFT-Leipzig",51.3520,12.435,125.0
"IHOP-Homestead",36.5580,-100.606,850.0
"Ilorin",8.32,4.34,350.0
"IMAA_Potenza",40.6000,15.72,820.0
"IMC_Oristano",39.91,8.5,10.0
"IMS-METU-ERDEMLI",36.5650,34.2550,3.0
"Inhaca",-26.041,32.9050,73.0
"Inner_Mongolia",42.6830,115.954,1343.0
"Iqaluit",63.7480,-68.5430,15.0
"Irkutsk",51.8000,103.087,670.0
"ISDGM_CNR",45.437,12.332,20.0
"Ispra",45.8030,8.627,235.0
"Issyk-Kul",42.6230,76.9830,1650.0
"Izana",28.309,-16.4990,2391.0
"Jabal_Hafeet",24.0580,55.7760,1059.0
"Jabiru",-12.661,132.893,30.0
"Jamari",-8.633,-62.75,100.0
"Jaru_Reserve",-10.083,-61.9330,162.0
"Ji_Parana",-10.86,-61.8000,100.0
"Ji_Parana_SE",-10.934,-62.8520,218.0
"Ji_Parana_UNIR",-10.883,-61.9670,100.0
"Joberg",-26.1860,28.0290,1736.0
"JonesERC",31.2310,-84.4710,50.0
"Jornada",32.3510,-106.517,1288.0
"Jug_Bay",38.7670,-76.778,10.0
"Kaashidhoo",4.965,73.4660,0.0
"Kaiping",22.3150,112.539,51.0
"Kaloma",-14.86,24.8280,1230.0
"Kandahar",31.5090,65.848,1007.0
"Kangerlussuaq",66.9960,-50.6210,320.0
"Kanpur",26.513,80.2320,123.0
"Kanzelhohe_Obs",46.6780,13.907,1526.0
"Kaoma",-14.793,24.795,1179.0
"Karachi",24.8700,67.0300,49.0
"Karlsruhe",49.0930,8.428,140.0
"Kasama",-10.167,31.1830,1300.0
"Kathmandu_Univ",27.601,85.5380,1510.0
"Katibougou",12.917,-7.532,0.0
"Kejimkujik",44.3830,-65.2830,154.0
"Kellogg_LTER",42.4080,-85.3720,293.0
"Kelowna",49.9550,-119.373,344.0
"Key_Biscayne",25.732,-80.1630,0.0
"Kibale",0.56,30.358,1536.0
"Kolfield",39.8020,-74.4760,50.0
"Kolimbari",35.5330,23.7830,0.0
"KONZA_EDC",39.1020,-96.6100,341.0
"Krasnoyarsk",55.9830,92.7670,202.0
"Kuopio",62.8920,27.6340,105.0
"Kuujjuarapik",55.3000,-77.8000,0.0
"Kuwait_University",29.3250,47.9710,42.0
"Kyiv",50.3640,30.497,200.0
"La_Crau",43.577,4.819,32.0
"La_Jolla",32.8700,-117.25,115.0
"La_Laguna",28.482,-16.3210,568.0
"La_Parguera",17.9700,-67.0450,12.0
"La_Paz",-16.539,-68.0660,3439.0
"Laegeren",47.48,8.351,735.0
"Lake_Argyle",-16.108,128.749,150.0
"Lampedusa",35.5170,12.632,45.0
"Lanai",20.7350,-156.922,20.0
"Lannion",48.7310,-3.462,15.0
"Le_Fauga",43.3840,1.285,193.0
"Lecce_University",40.3350,18.111,30.0
"Leicester",52.6190,-1.122,89.0
"Liangning",41.5120,122.701,15.0
"Lille",50.612,3.142,60.0
"Lochiel",49.028,-122.602,0.0
"Longyearbyen",78.223,15.649,30.0
"Los_Alamos",35.8740,-106.326,2350.0
"Los_Fieros",-14.55,-60.6170,225.0
"LOS_FIEROS_98",-14.556,-60.9290,170.0
"Lulin",23.469,120.874,2868.0
"Lunar_Lake",38.3900,-115.988,1908.0
"LW-SCAN",34.9600,-97.9790,358.0
"MAARCO",24.7000,54.659,10.0
"Mace_Head",53.3300,-9.9,20.0
"Madison",43.07,-89.4100,326.0
"Mainz",49.9990,8.3,150.0
"Malaga",36.715,-4.478,40.0
"MALE",4.192,73.5290,2.0
"Manaus",-2.599,-60.0390,93.0
"Maricopa",33.069,-111.972,360.0
"Marseille",43.2820,5.384,100.0
"Maun_Tower",-19.9,23.5500,940.0
"Mauna_Loa",19.539,-155.578,3397.0
"MCO-Hanimaadhoo",6.776,73.1830,0.0
"MD_Science_Center",39.2830,-76.6170,15.0
"Merredin",-31.493,118.226,315.0
"Messina",38.1970,15.567,15.0
"Mexico_City",19.334,-99.1820,2268.0
"Mezaira",23.145,53.7790,204.0
"Mfuwe",-13.257,31.931,550.0
"Midway_Island",28.2100,-177.378,20.0
"Milyering",-22.0290,113.923,10.0
"Minsk",53.9200,27.601,200.0
"MISR-JPL",34.1990,-118.174,367.0
"Missoula",46.917,-114.083,1028.0
"Modena",44.632,10.945,56.0
"Moldova",47.0,28.816,205.0
"Mongu",-15.254,23.1510,1107.0
"Mont_Joli",48.6400,-68.1560,30.0
"Monterey",36.5930,-121.855,50.0
"Moscow_MSU_MO",55.7000,37.5100,192.0
"Moss_Landing",36.7930,-121.788,20.0
"Mount_Chacaltaya",-16.35,-68.1320,5233.0
"Mount_Gibbes",35.7830,-82.2930,2006.0
"Mukdahan",16.607,104.676,166.0
"Munich_Maisach",48.209,11.258,520.0
"Munich_University",48.1480,11.573,533.0
"Muscat",23.6060,58.4360,22.0
"Mussafa",24.372,54.4670,10.0
"MVCO",41.3000,-70.5500,10.0
"Mwinilunga",-11.74,24.431,1430.0
"Nainital",29.3590,79.458,1939.0
"Nairobi",-1.339,36.8650,1650.0
"NAM_CO",30.7730,90.9620,4740.0
"NASA_Ames",37.4200,-122.057,10.0
"NASA_LaRC",37.105,-76.3790,5.0
"Nauru",-0.521,166.916,7.0
"NCU_Taiwan",24.9670,121.192,171.0
"Ndola",-12.995,28.6580,1270.0
"Nes_Ziona",31.9220,34.7890,40.0
"New_Delhi",28.6300,77.1750,240.0
"Niabrara",42.7650,-100.020,730.0
"Niamey",13.481,2.172,205.0
"Nicelli_Airport",45.4260,12.382,13.0
"Norfolk_State_Univ",36.848,-76.2590,20.0
"Noto",37.334,137.137,200.0
"NSA_YJP_BOREAS",55.903,-98.2900,290.0
"Ny_Alesund",78.9290,11.861,46.0
"OBERNAI",48.4430,7.543,161.0
"OceolaNF",30.205,-82.4430,0.0
"OHP_OBSERVATOIRE",43.9350,5.71,680.0
"OK_St_Univ",35.0460,-97.917,331.0
"OkefenokeeNWR",30.7410,-82.1290,0.0
"Okinawa",26.357,127.768,46.0
"Omkoi",17.798,98.4320,1120.0
"Oostende",51.2250,2.925,23.0
"OPAL",79.9900,-85.9390,0.0
"Osaka",34.6510,135.591,50.0
"Ouagadougou",12.2,-1.4,290.0
"Owens_Lake",36.4880,-117.871,1167.0
"Oyster",37.2950,-75.9330,8.0
"Paddockwood",53.5,-105.5,503.0
"Palaiseau",48.7000,2.208,156.0
"Palencia",41.9890,-4.516,750.0
"Palgrunden",58.7550,13.152,49.0
"Panama_BCI",9.167,-79.8500,0.0
"Pantnagar",29.046,79.5210,241.0
"Paposo",-25.007,-70.4500,0.0
"Paris",48.8670,2.333,50.0
"PEARL",80.0540,-86.417,615.0
"Penn_State_Univ",40.7420,-78.0810,401.0
"Perth",-32.0080,115.894,0.0
"Petrolina_SONDA",-9.383,-40.5,370.0
"Philadelphia",40.0360,-75.0050,20.0
"Pickle_Lake",51.4490,-90.2180,393.0
"Pietersburg",-23.8830,29.4500,1200.0
"Pimai",15.182,102.564,220.0
"Pitres",36.9330,-3.222,1252.0
"PKU_PEK",39.5930,116.184,66.0
"Porquerolles",43.0010,6.161,10.0
"Porto_Nacional",-11.0,-48.0,210.0
"Porto_Velho",-8.77,-63.9500,110.0
"Potosi_Mine",-9.283,-62.8670,80.0
"Praia",14.947,-23.4840,70.0
"Prospect_Hill",32.3700,-64.6960,63.0
"Puspiptek",-6.356,106.664,15.0
"Quarzazate",30.9390,-6.909,1150.0
"Ragged_Point",13.165,-59.4320,40.0
"Railroad_Valley",38.5040,-115.962,1435.0
"Rame_Head",50.3660,-4.149,0.0
"Ras_El_Ain",31.67,-7.599,570.0
"Realtor",43.486,5.384,208.0
"Red_Bluff",40.1500,-122.25,40.0
"Red_Mountain_Pass",37.9080,-107.725,3368.0
"Resolute_Bay",74.7330,-94.9000,40.0
"REUNION_ST_DENIS",-20.8830,55.4830,0.0
"Richland",46.34,-119.280,123.0
"Rimrock",46.487,-116.992,824.0
"Rio_Branco",-9.957,-67.8690,212.0
"Rio_Piedras",18.402,-66.0510,30.0
"Rochester",44.2340,-77.5860,0.0
"Rogers_Dry_Lake",34.9260,-117.885,680.0
"Rome_Tor_Vergata",41.84,12.647,130.0
"Roosevelt_Roads",18.2000,-65.6000,10.0
"Rossfeld",48.3350,7.625,167.0
"Rottnest_Island",-32.0,115.502,70.0
"Saada",31.6260,-8.156,420.0
"Saih_Salam",24.829,55.313,84.0
"Saint_Mandrier",43.0670,5.944,44.0
"San_Nicolas",33.257,-119.487,133.0
"Sandy_Hook",40.4480,-73.9930,0.0
"SANTA_CRUZ",-17.802,-63.1780,442.0
"Santa_Cruz_Tenerife",28.473,-16.247,52.0
"SANTA_CRUZ_UTEPSA",-17.767,-63.201,432.0
"Santarem",-2.433,-54.75,70.0
"Santiago",-33.4900,-70.7170,510.0
"Sao_Paulo",-23.5610,-46.7350,865.0
"Saturn_Island",48.7830,-123.133,200.0
"SEDE_BOKER",30.855,34.7820,480.0
"Senanga",-16.1090,23.2930,1025.0
"Seoul_SNU",37.458,126.951,116.0
"SERC",38.8830,-76.5,10.0
"Sesheke",-17.4810,24.3040,951.0
"Sevastopol",44.6160,33.5170,80.0
"Sevilleta",34.355,-106.885,1477.0
"Shelton",40.75,-98.7600,563.0
"Shirahama",33.6930,135.357,10.0
"Silpakorn_Univ",13.819,100.041,72.0
"Singapore",1.298,103.780,30.0
"Sioux_Falls",43.736,-96.6260,500.0
"Sioux_Falls_X",43.736,-96.6260,500.0
"Sir_Bu_Nuair",25.2170,54.2330,10.0
"Skukuza",-24.9920,31.587,150.0
"SKUKUZA_AEROPORT",-24.969,31.593,293.0
"SMART",24.2490,55.612,250.0
"SMART_POL",24.2490,55.612,250.0
"SMEX",41.9360,-93.6640,316.0
"SMHI",58.5800,16.15,0.0
"Sodankyla",67.3670,26.6300,184.0
"Solar_Village",24.907,46.3970,764.0
"Solwezi",-12.171,26.3630,1333.0
"Sopot",54.451,18.5650,0.0
"South_Pole_Obs_NOAA",-89.9960,70.3000,2850.0
"Spokane",47.6200,-117.534,360.0
"SS_OJP_BOREAS",53.916,-104.690,500.0
"SSA_YJP_BOREAS",53.6750,-104.650,490.0
"Stennis",30.368,-89.6170,20.0
"Sterling",38.9830,-77.4670,50.0
"Sua_Pan",-20.5330,26.0670,900.0
"Suffield",50.2820,-111.131,761.0
"Surinam",5.8,-55.2000,0.0
"Swakopmund",-22.6580,14.564,250.0
"T0_MAX_MEX",19.49,-99.1480,2257.0
"T1_MAX_MEX",19.7030,-98.9820,2272.0
"Table_Mountain",40.125,-105.237,1689.0
"TABLE_MOUNTAIN_CA",34.3800,-117.68,2200.0
"Tahiti",-17.577,-149.606,98.0
"Taichung",24.1060,120.491,10.0
"Taihu",31.421,120.215,20.0
"Taipei_CWB",25.0300,121.5,26.0
"Tamanrasset_TMP",22.7900,5.53,1377.0
"Tamihua",21.261,-97.4420,10.0
"Tampico_MAX_MEX",22.278,-97.8640,15.0
"Tarbes",43.25,0.083,350.0
"Tenerife",28.0330,-16.6330,10.0
"Tenosique",17.4880,-91.4260,20.0
"THALA",35.5500,8.683,1091.0
"The_Hague",52.1100,4.327,18.0
"Thessaloniki",40.6300,22.9600,60.0
"Thompson",55.8000,-97.8500,218.0
"Thompson_Farm",43.1090,-70.9480,26.0
"Thule",76.5160,-68.7690,225.0
"Tinga_Tingana",-28.976,139.991,38.0
"Tombstone",31.7420,-110.050,1408.0
"Tomsk",56.4770,85.0470,130.0
"Tonopah_Airport",38.0500,-117.091,1580.0
"Toravere",58.2550,26.4600,70.0
"Toronto",43.9700,-79.4700,300.0
"Toulon",43.1360,6.009,50.0
"TOULOUSE",43.562,1.476,150.0
"Trelew",-43.25,-65.3090,15.0
"Tremiti",42.118,15.49,4.0
"Trinidad_Head",41.0540,-124.151,105.0
"Tucson",32.2330,-110.953,779.0
"Tudor_Hill",32.264,-64.8790,51.0
"Tukurui",-3.717,-49.6830,100.0
"Tuxtla_Gutierrez",16.7550,-93.152,590.0
"UAHuntsville",34.7250,-86.6450,223.0
"Uberlandia",-18.9,-48.2830,850.0
"UCLA",34.07,-118.450,131.0
"UCSB",34.4150,-119.845,33.0
"Ukiah",45.1340,-118.919,1100.0
"Ulaangom",49.973,92.0780,1363.0
"Umm_Al_Quwain",25.5330,55.6580,20.0
"Univ_of_Houston",29.718,-95.3420,65.0
"USDA",39.0300,-76.8800,50.0
"USDA-BARC",39.0310,-76.9320,46.0
"USDA-Howard",39.0540,-76.8770,52.0
"Ussuriysk",43.7000,132.163,280.0
"Venise",45.3140,12.508,10.0
"Villefranche",43.6840,7.329,130.0
"Vinon",43.709,5.759,304.0
"Vishkhapatnam",17.7240,83.3270,30.0
"Walker_Branch",35.958,-84.2870,365.0
"Wallops",37.9420,-75.4750,10.0
"Waskesiu",53.917,-106.083,550.0
"White_Sands_HELSTF",32.6350,-106.338,1207.0
"Windsor_B",42.2830,-83.083,200.0
"Wits_University",-26.1920,28.0290,1775.0
"Xanthi",41.1470,24.9190,54.0
"XiangHe",39.7540,116.962,36.0
"Xinglong",40.396,117.578,970.0
"Yakutsk",61.6620,129.367,118.0
"Yaqui",27.281,-109.912,40.0
"Yekaterinburg",57.0380,59.5450,300.0
"Yellowknife",62.452,-114.407,201.0
"Yufa_PEK",39.3090,116.184,20.0
"Yulin",38.2830,109.717,1080.0
"Zambezi",-13.533,23.107,1040.0
"Zinder_DMN",13.775,8.984,460.0
"Zvenigorod",55.695,36.7750,200.0
</granules>
            </location_dim>
            <time_dim dim_type="time">
                <default_cursor>2006-10-01</default_cursor>
                <sample_periodicity_multiplier>1</sample_periodicity_multiplier>
                <sample_periodicity_unit>hour</sample_periodicity_unit>
                <sample_duration>1</sample_duration>
                <time_min>1993-05-15</time_min>
                <time_max>2009-08-11</time_max>
            </time_dim>
        </dimensions>
        <views>
            <map_view view_type="map_view">
                <zoom lon_min="-180" lon_max="170" lat_min="-50" lat_max="80" />
                <LocPoint>
                    <access>
                        <access_instructions>common</access_instructions>
                        <data_access_class>map_time_view</data_access_class>
                        <retrieved_data_type>POINT</retrieved_data_type>
                    </access>
                </LocPoint>
            </map_view>
            <time_view view_type="time_view">
                <zoom time_min="1993-05-15" time_max="2009-01-01" />
                <TimePoint>
                    <access>
                        <access_instructions>common</access_instructions>
                        <data_access_class>map_time_view</data_access_class>
                        <retrieved_data_type>POINT</retrieved_data_type>
                    </access>
                </TimePoint>
            </time_view>
            <map_time_view view_type="map_time_view">
                <MapTimePoint>
                    <access>
                        <access_instructions>
                            server=sqlbox.me.wustl.edu;database=AERONET;uid=SQLLBOX_uid;pwd=SQLLBOX_passwd::
                            select
                            location.lat,
                            location.lon,
                            location.loc_code,
                            [[param_abbr]].datetime,
                            [[param_abbr]].[[param_abbr]] as [[param_abbr]]
                            from location
                            inner join [[param_abbr]] on [[param_abbr]].loc_id = location.loc_id
                            where
                            ([[param_abbr]].datetime between '[[datetime_min]]' and '[[datetime_max]]')
                            and (location.lat between [[lat_min]] and [[lat_max]])
                            and (location.lon between [[lon_min]] and [[lon_max]])
                            and (([[do_compare_locs]]=0) or (location.loc_code in ([[loc_code_list]])))
                            and (([[do_compare_times]]=0) or ([[param_abbr]].datetime in ([[datetime_list]])))
                            [[sql_filter]]
                            order by [[param_abbr]].datetime asc, location.lon asc, location.lat asc;
                        </access_instructions>
                        <data_access_class>SQL</data_access_class>
                        <retrieved_data_type>POINT</retrieved_data_type>
                    </access>
                </MapTimePoint>
            </map_time_view>
            <param_view view_type="param_view">
                <ParamPoint>
                    <access>
                        <access_instructions>
                            server=sqlbox.me.wustl.edu;database=AERONET;uid=dataro;pwd=dataro::
                            select loc_code, lat, lon, '[[datetime]]' as [datetime],
                            Angstrom_440_870 as [440-870 Angstrom],
                            Angstrom_380_500 as [380-500 Angstrom],
                            Angstrom_440_675 as [440-675 Angstrom],
                            Angstrom_500_870 as [500-870 Angstrom],
                            Angstrom_340_440 as [340-440 Angstrom],
                            Angstrom_440_675_Polar as [440-675Angstrom(Polar)],
                            AOT_1640 as [AOT_1640],
                            AOT_1020 as [AOT_1020],
                            AOT_870 as [AOT_870],
                            AOT_675 as [AOT_675],
                            AOT_667 as [AOT_667],
                            AOT_555 as [AOT_555],
                            AOT_551 as [AOT_551],
                            AOT_532 as [AOT_532],
                            AOT_500 as [AOT_500],
                            AOT_490 as [AOT_490],
                            AOT_443 as [AOT_443],
                            AOT_440 as [AOT_440],
                            AOT_412 as [AOT_412],
                            AOT_380 as [AOT_380],
                            AOT_340 as [AOT_340],
                            Water as [Water(cm)],
                            TripletVar_1640 as [%TripletVar 1640],
                            TripletVar_1020 as [%TripletVar 1020],
                            TripletVar_870 as [%TripletVar 870],
                            TripletVar_675 as [%TripletVar 675],
                            TripletVar_667 as [%TripletVar 667],
                            TripletVar_555 as [%TripletVar 555],
                            TripletVar_551 as [%TripletVar 551],
                            TripletVar_532 as [%TripletVar 532],
                            TripletVar_500 as [%TripletVar 500],
                            TripletVar_490 as [%TripletVar 490],
                            TripletVar_443 as [%TripletVar 443],
                            TripletVar_440 as [%TripletVar 440],
                            TripletVar_412 as [%TripletVar 412],
                            TripletVar_380 as [%TripletVar 380],
                            TripletVar_340 as [%TripletVar 340]
                            from location
                            left outer join Angstrom_440_870 on Angstrom_440_870.loc_id = location.loc_id and Angstrom_440_870.[datetime] = '[[datetime]]'
                            left outer join Angstrom_380_500 on Angstrom_380_500.loc_id = location.loc_id and Angstrom_380_500.[datetime] = '[[datetime]]'
                            left outer join Angstrom_440_675 on Angstrom_440_675.loc_id = location.loc_id and Angstrom_440_675.[datetime] = '[[datetime]]'
                            left outer join Angstrom_500_870 on Angstrom_500_870.loc_id = location.loc_id and Angstrom_500_870.[datetime] = '[[datetime]]'
                            left outer join Angstrom_340_440 on Angstrom_340_440.loc_id = location.loc_id and Angstrom_340_440.[datetime] = '[[datetime]]'
                            left outer join Angstrom_440_675_Polar on Angstrom_440_675_Polar.loc_id = location.loc_id and Angstrom_440_675_Polar.[datetime] = '[[datetime]]'
                            left outer join AOT_1640 on AOT_1640.loc_id = location.loc_id and AOT_1640.[datetime] = '[[datetime]]'
                            left outer join AOT_1020 on AOT_1020.loc_id = location.loc_id and AOT_1020.[datetime] = '[[datetime]]'
                            left outer join AOT_870 on AOT_870.loc_id = location.loc_id and AOT_870.[datetime] = '[[datetime]]'
                            left outer join AOT_675 on AOT_675.loc_id = location.loc_id and AOT_675.[datetime] = '[[datetime]]'
                            left outer join AOT_667 on AOT_667.loc_id = location.loc_id and AOT_667.[datetime] = '[[datetime]]'
                            left outer join AOT_555 on AOT_555.loc_id = location.loc_id and AOT_555.[datetime] = '[[datetime]]'
                            left outer join AOT_551 on AOT_551.loc_id = location.loc_id and AOT_551.[datetime] = '[[datetime]]'
                            left outer join AOT_532 on AOT_532.loc_id = location.loc_id and AOT_532.[datetime] = '[[datetime]]'
                            left outer join AOT_500 on AOT_500.loc_id = location.loc_id and AOT_500.[datetime] = '[[datetime]]'
                            left outer join AOT_490 on AOT_490.loc_id = location.loc_id and AOT_490.[datetime] = '[[datetime]]'
                            left outer join AOT_443 on AOT_443.loc_id = location.loc_id and AOT_443.[datetime] = '[[datetime]]'
                            left outer join AOT_440 on AOT_440.loc_id = location.loc_id and AOT_440.[datetime] = '[[datetime]]'
                            left outer join AOT_412 on AOT_412.loc_id = location.loc_id and AOT_412.[datetime] = '[[datetime]]'
                            left outer join AOT_380 on AOT_380.loc_id = location.loc_id and AOT_380.[datetime] = '[[datetime]]'
                            left outer join AOT_340 on AOT_340.loc_id = location.loc_id and AOT_340.[datetime] = '[[datetime]]'
                            left outer join Water on Water.loc_id = location.loc_id and Water.[datetime] = '[[datetime]]'
                            left outer join TripletVar_1640 on TripletVar_1640.loc_id = location.loc_id and TripletVar_1640.[datetime] = '[[datetime]]'
                            left outer join TripletVar_1020 on TripletVar_1020.loc_id = location.loc_id and TripletVar_1020.[datetime] = '[[datetime]]'
                            left outer join TripletVar_870 on TripletVar_870.loc_id = location.loc_id and TripletVar_870.[datetime] = '[[datetime]]'
                            left outer join TripletVar_675 on TripletVar_675.loc_id = location.loc_id and TripletVar_675.[datetime] = '[[datetime]]'
                            left outer join TripletVar_667 on TripletVar_667.loc_id = location.loc_id and TripletVar_667.[datetime] = '[[datetime]]'
                            left outer join TripletVar_555 on TripletVar_555.loc_id = location.loc_id and TripletVar_555.[datetime] = '[[datetime]]'
                            left outer join TripletVar_551 on TripletVar_551.loc_id = location.loc_id and TripletVar_551.[datetime] = '[[datetime]]'
                            left outer join TripletVar_532 on TripletVar_532.loc_id = location.loc_id and TripletVar_532.[datetime] = '[[datetime]]'
                            left outer join TripletVar_500 on TripletVar_500.loc_id = location.loc_id and TripletVar_500.[datetime] = '[[datetime]]'
                            left outer join TripletVar_490 on TripletVar_490.loc_id = location.loc_id and TripletVar_490.[datetime] = '[[datetime]]'
                            left outer join TripletVar_443 on TripletVar_443.loc_id = location.loc_id and TripletVar_443.[datetime] = '[[datetime]]'
                            left outer join TripletVar_440 on TripletVar_440.loc_id = location.loc_id and TripletVar_440.[datetime] = '[[datetime]]'
                            left outer join TripletVar_412 on TripletVar_412.loc_id = location.loc_id and TripletVar_412.[datetime] = '[[datetime]]'
                            left outer join TripletVar_380 on TripletVar_380.loc_id = location.loc_id and TripletVar_380.[datetime] = '[[datetime]]'
                            left outer join TripletVar_340 on TripletVar_340.loc_id = location.loc_id and TripletVar_340.[datetime] = '[[datetime]]'
                            WHERE location.loc_code='[[loc_code]]'
                        </access_instructions>
                        <data_access_class>SQL</data_access_class>
                        <retrieved_data_type>TABLE</retrieved_data_type>
                    </access>
                </ParamPoint>
            </param_view>
        </views>
    </PointParamLocTime>
</dataset>