UV station data based on operational
TEMIS satellite ozone data

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UV archive
overview

UV index main page  |  UV dose main page
 

Time series of UV data

Time series UV index and UV dose data derived from the operational TEMIS assimilates ozone data -- so-called overpass files -- are generated from the UV data archive for selected places.

For all stations the overpass file contains the cloud-free UV index and UV dose data (starting 1 July 2002). For stations inside the MSG data area, see the 4th column, there is in principle also cloud-modified UV dose data in the overpass file (MSG data is available since 24 Jan. 2004).

Information on the structure of the data files is given below the table.

 

station/place name
(click to download ascii file)
longitude latitude MSG area
AcadiaNatForest, USA -68.30 44.40 no
Adana, Turkey 35.35 36.98 yes
Adelaide, Australia 138.62 -34.92 no
Ahmedabad, India 72.67 23.05 no
Alert, Canada -62.35 82.47 no
AliceSprings, Australia 133.90 -23.80 no
Andoya, Norway 16.00 69.30 no
Angra_do_Heroismo, Azores_Portugal -27.22 38.66 yes
Ankara, Turkey 32.88 39.95 yes
Antalya, Turkey 30.73 36.87 yes
Arica, Chile -70.31 -18.47 no
Arosa, Switzerland 9.67451 46.77916 yes
Atlanta, USA -84.40 33.70 no
Aulnay_Paris, France -0.35 46.02 yes
Baghdad, Iraq 44.43 33.30 yes
Bangalore, India 77.59 12.97 no
Baoding, China 115.46 38.87 no
Barrow, USA -156.60 71.32 no
Belsk, Poland 20.78 51.83 yes
Bhopal, India 77.47 23.28 no
Bilthoven, Netherlands 5.20 52.12 yes
Bordeaux, France -0.53 44.84 yes
Boulder, USA -105.30 40.00 no
Briancon, France 6.65 44.90 yes
Brisbane, Australia 153.03 -27.45 no
Brno, Czechia 16.60 49.20 yes
Buenos_Aires, Argentina -58.48 -34.58 yes
Calgary, Canada -114.084 51.084 no
Camborne, GreatBritain -5.30 50.20 yes
Canyonlands, USA -109.80 38.50 no
Carrollton, USA -96.89 32.95 no
Casey, Australia 110.53 -66.28 no
Chengkung, Taiwan 121.34 23.07 no
Chennai, India 80.30 13.08 no
Churchill, Canada -94.00 58.75 no
Clark_New_Jersey, USA -74.31 40.64 no
Dalian, China 121.36 38.54 no
Darwin, Australia 130.89 -12.43 no
Davis, Australia 77.97 -68.58 no
Davos, Switzerland 9.8435 46.8130 yes
DeBilt, Netherlands 5.18 52.10 yes
Denali, USA -149.00 63.70 no
Dublin, Ireland -6.2489 53.3331 yes
Durban, SouthAfrica 30.98 -29.87 yes
Edinburgh, GreatBritain -3.1965 55.9521 yes
Edmonton, Canada -114.10 53.55 no
Erzurum, Turkey 41.17 39.95 yes
Eureka, Canada -86.43 80.05 no
Everglades, USA -80.70 25.40 no
FortWilliam, GreatBritain -5.1121 56.8165 yes
Funchal, Madeira_Portugal -16.89 32.64 yes
Gaithersburg, USA -77.20 39.10 no
Galway, Ireland -9.0489 53.2719 yes
Garmisch, Germany 11.07 47.48 yes
GooseBay, Canada -60.30 53.23 no
GreatSmokeyMtns, USA -83.80 35.60 no
Halifax, Canada -63.66 44.73 no
Haute_Provence, France 5.7 43.94 yes
Havana, Cuba -82.38 23.12 no
Hilla_Babylon, Iraq 44.41 32.50 yes
Hohenpeissenberg, Germany 11.02 47.80 yes
HradecKralove, CzechRepublic 15.83 50.19 yes
Hyderabad, India 78.43 17.37 no
Invercargill, NewZealand 168.33 -46.42 no
Ispra, Italy 8.63 45.81 yes
Istanbul, Turkey 28.82 40.97 yes
Izana, Tenerife_Spain -16.50 28.49 yes
Izmir, Turkey 27.02 38.52 yes
Jokioinen, Finland 23.50 60.81 yes
Jungfraujoch, Switzerland 7.9853 46.5474 yes
Kagoshima, Japan 130.50 31.50 no
Kayseri, Turkey 35.42 38.82 yes
Kingston, Australia 147.29 -42.99 no
Kolkata, India 88.33 22.50 no
La_Quiaca, Argentina -65.60 -22.10 yes
LabskaBouda, CzechRepublic 15.55 50.76 yes
Lampedusa, Italy 12.60 35.50 yes
Lauder, NewZealand 169.68 -45.04 no
Leba, Poland 17.53 54.75 yes
Legionowo, Poland 20.97 52.40 yes
Leigh, NewZealand 175.00 -36.50 no
Lindenberg, Germany 14.12 52.21 yes
Lisbon, Portugal -9.15 38.77 yes
Locarno, Switzerland 8.7874 46.1726 yes
Lyon, France 4.834 45.768 yes
Macquerie_Island, Australia 158.94 -54.50 no
Maitri, Antarctica 11.75 -70.75 no
Malta_airport, Malta 14.48 35.85 yes
Manchester, GreatBritain -2.23 53.28 yes
Mar_del_Plata, Argentina -57.524 -38.017 yes
Marambio, Argentina -64.24 -56.62 no
Mardin, Turkey 40.73 37.30 yes
MaunaLoa, USA -155.58 19.53 no
Mawson, Australia 62.87 -67.60 no
Mecca, Saudi_Arabia 39.82 21.42 yes
Melbourne, Australia 145.10 -37.73 no
Mendel_Ross_Island, Antarctica -57.88 -63.80 no
Mendoza, Argentina -68.50 -32.53 no
Mil.-Airport_Tatoi, Greece 23.78 38.11 yes
Montreal, Canada -73.75 45.47 no
Moscow, Russia 37.50 55.70 yes
MountWaliguan, China 100.90 36.30 no
Mugla, Turkey 28.37 37.22 yes
Mumbai, India 72.85 18.93 no
Nadi, Fiji 177.45 -17.76 no
Naha, Japan 127.65 26.17 no
Nashville_Airport, USA -86.68 36.12 no
Nea_Mihaniona, Greece 22.85 40.47 yes
Neuherberg, Germany 11.58 48.22 yes
New_Delhi, India 77.22 28.62 no
Newcastle, Australia 151.72 -32.90 no
Norrkoping, Sweden 16.15 58.58 yes
Obninsk, Russia 55.09 35.97 yes
Oesteraas, Norway 10.75 59.92 yes
Offenbach, Germany 8.65 50.01 yes
Oslo, Norway 10.717 59.938 yes
Palmer, Antarctica -64.00 -64.70 no
Paramaribo, Surinam -55.20 5.75 yes
Paraparaumu, NewZealand 174.98 -40.90 no
Paris, France 2.34 48.85 yes
Payerne, Switzerland 6.9424 46.8116 yes
Penhas_Douradas, Portugal -7.55 40.58 yes
Perth, Australia 115.96 -31.92 no
Pilar, Argentina -63.88 -31.66 yes
Pohang, Korea 129.35 36.00 no
Poprad-Ganovce, Slovakia 20.29 49.00 yes
Potsdam, Germany 13.08 52.36 yes
Pucallpa, Peru -74.55 -8.38 no
Puerto_Madryn, Argentina -64.811 -42.595 no
Puerto_Quequa, Argentina -58.637 -38.566 yes
Pune, India 73.80 18.52 no
PuntaArenas, Chile -70.90 -53.00 no
Rarotonga, CookIslands -159.80 -21.20 no
Reading, GreatBritain -0.93 51.45 yes
Regina_BrattsLake, Canada -104.74 50.18 no
ResearchTrianglePk, USA -78.90 35.90 no
Resolute, Canada -95.01 74.69 no
Reunion, France 55.5 -20.94 yes
Rio_Gallegos, Argentina -69.32 -51.60 no
Rio_Negro, Argentina -62.890 -41.081 no
Rize, Turkey 40.52 41.03 yes
RockyMountain, USA -105.50 40.00 no
Rome, Italy 12.52 41.90 yes
SaintPetersburg, USA -82.68 27.77 no
Samsun, Turkey 36.3 41.28 yes
SanDiego, USA -117.11 32.45 no
SanFrancisco, USA -122.42 37.78 no
Santiago, Chile -70.6545 -33.42 no
SaoPaulo, Brazil -46.64 -23.55 yes
Sapporo, Japan 141.30 43.02 no
Saskatoon, Canada -106.71 52.11 no
SaturnaIsland, Canada -123.13 48.78 no
Seoul, South_Korea 127.03 37.35 no
Shenandoah, USA -78.40 38.50 no
Sodankyla, Finland 26.63 67.37 no
Sonnblick, Austria 12.95 47.05 yes
Srinagar, India 74.83 34.13 no
Stockholm, Sweden 18.08 59.33 yes
Sulaimaniya, Iraq 45.43 35.55 yes
Sydney, Australia 151.10 -34.04 no
Syowa, Japan 39.55 -69.03 no
Taipei, Taiwan 121.49 24.99 no
Tarija, Bolivia -64.721 -21.543 yes
Tartu, Estonia 26.50 58.30 yes
Tateno_Tsukuba, Japan 140.07 36.02 no
Tehran, Iran 51.43 35.67 yes
Tel_Aviv, Israel 34.77 32.070 yes
Thessaloniki, Greece 22.96 40.63 yes
Tianjin, China 117.20 39.08 no
Tokyo, Japan 139.67 35.65 no
Toowoomba, Australia 151.55 -27.22 no
Toronto, Canada -79.47 43.78 no
Townsville, Australia 146.76 -19.33 no
Tromso, Norway 18.93 69.66 no
Trondheim, Norway 10.47 63.43 yes
Uccle, Belgium 4.36 50.80 yes
Ushuaia, Argentina -68.31 -54.85 no
Valdivia, Chile -73.15 -39.48 no
Valparaiso, Chile -71.620 -33.040 no
Van, Turkey 43.32 38.45 yes
Venice, Italy 12.33 45.43 yes
Vienna, Austria 16.35 48.23 yes
VilleneuvedAscq, France 3.14 50.61 yes
Vindeln, Sweden 19.77 64.23 yes
VirginIslands, USA -64.80 18.30 yes
Winnipeg, Canada -97.24 49.91 no
Zakopane, Poland 19.97 49.30 yes
Zugspitze, Germany 10.98 47.42 yes

 

The MSG data area is marked by light grey,
the location of the stations by red dots.

 
 

Data description

The header of an overpass file details contents and structure of the file:

# TEMIS v2.0 UV index and UV dose overpass file
# =============================================
# http://www.temis.nl/uvradiation/UVarchive/stations_uv.html
#
# Station name     = Zugspitze
# Station country  = Germany
# Station lon, lat = 10.98, 47.42
#
# Grid cell size              = 0.25 x 0.25 degrees
# Grid cell centre lon, lat   = 10.875, 47.375
# Grid cell average elevation = 1390 (+/- 424) m
# Grid cell within MSG area   = yes
#
# Data columns:
#      1 = YYYYMMDD        : date string
#   2, 3 = UVIEF, UVIEFerr : cloud-free erythemal UV index      [-]
#   4, 5 = UVDEF, UVDEFerr : cloud-free     erythemal  UV dose  [kJ/m2]
#   6, 7 = UVDEC, UVDECerr : cloud-modified erythemal  UV dose  [kJ/m2]
#   8, 9 = UVDVF, UVDVFerr : cloud-free     vitamin-D  UV dose  [kJ/m2]
#  10,11 = UVDVC, UVDVCerr : cloud-modified vitamin-D  UV dose  [kJ/m2]
#  12,13 = UVDDF, UVDDFerr : cloud-free     dna-damage UV dose  [kJ/m2]
#  14,15 = UVDDC, UVDDCerr : cloud-modified dna-damage UV dose  [kJ/m2]
#     16 = CMF             : average cloud modification factor  [-]
#     17 = ozone           : local solar noon ozone column      [DU]
#
# No-data entry = -1.000
#
#
# YYYYMMDD    UVIEF UVIEFerr  UVDEF UVDEFerr  UVDEC UVDECerr  ...   CMF    ozone
  20020701    8.752   0.526   5.180   0.354  -1.000  -1.000   ...  -1.000  313.2
  20020702    8.009   0.520   4.760   0.351  -1.000  -1.000   ...  -1.000  334.0
...

In case the station lies outside the MSG data area, the columns
with cloud-modified UV dose data have -1.000 throughout.   *)

The UV data is corrected for the effect of surface albedo on the surface UV radiation,
with the surface albedo is derived from a climatology; for details, see this page.

 
*) Note: The yes/no flag in the "MSG area" column of the table and comment line in the file header is based on the area covered by an MSG satellite in the default location (lon,lat)=(0,0). On days when a backup MSG satellite, located to the east or west, is used, stations just inside/outside the MSG perimeter may temporarily miss/have cloud-modified UV dose data.

 


last modified: 26 June 2017
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