Dallas Fort Worth airport is one of hundreds of GHCN reporting stations gone missing. GHCN stations are becoming an endangered species.
2010 Thermometer Langoliers Hit List
Guest post by E.M.Smith
Well, They Are At It Again
UPDATE 12 Feb 2010: Dallas has been found in the Failed QA file. Also, the “process” was discovered described in the ClimateGate emails by Phil Jones (see comments). The final update date is ill defined at best and this list ought to be treated as a “missing in action” list until the end of the month as we wait to see if further updates are applied. -E.M. Smith
Don’t know what to make of this list yet, other than it directly ‘gives the lie’ to the assertion that thermometer ‘drops’ were / are entirely an artifact of GHCN being a creation at a historical moment in time (i.e. made in 1990’s era so that’s why they drop out then in The Great Dying of Thermometers – which itself ignores The Lesser Dying in 2006).
It also shows that the excuse of things being dropped for not electronically reporting is pretty much a lie, too. I note that Dallas Fort Worth Airport is on this list and I’m pretty sure they have electronic reporting… From the NASA / GISS web site, as confirmation:
(*) Dallas-Fort W 32.9 N 97.0 W 425722590000 4,037,000 1947 – 2009
Note the end date of 2009.
And Strasbourg airport is on the list too, so it’s not just an America thing…
I’ve not examined this list for any patterns, nor re-done any of the prior “by latitude” and “by altitude” reports to see what the changes do to the world. For now, it’s just another “Dig Here” list. (Though a casual look at the altitude field shows a fair number of 1000m and 2000m stations died.)
Oh, and the list is also confirmation that the extraordinary hatred of thermometers shown by the managers of GHCN continues, unabated. Particular emphasis seems to have landed on Africa (already poorly covered) and Asia, with a modest effort to eradicate more of South America. By comparison, Europe is only slightly mauled…
[chiefio@Hummer data]$ wc -l 2009_uniq_station_list
1597 2009_uniq_station_list
[chiefio@Hummer data]$ wc -l 2010_uniq_station_list
1113 2010_uniq_station_list
So from 1597 we drop to 1113. That’s a drop of 30%.
Just shy of 1/3 of the stations, taken out back and shot this year.
But once you decided that you can just make up any missing data, then who needs to actually read the thermometers any more?
Ok, enough of my complaint. Here is the list. If anyone notices anything interesting about their part of the world, feel free to let us all know. Remember that the StationID (that first field) is structured as 1 digit of continent then 2 that tell the particular country, then 8 for the particular station and substation. So records that start with 1 are Africa, 2 Asia, 3 South America, 4 North America, 5 Pacific, 6 Europe, 7 Antarctica, 8 Ships at sea (a very few geographic spots with few records as a ship happens by and reports). I will break up the list into groups by continent, but notice that there are no “8″ stations on the list and only one from Antarctica. Oh, and there were 2 stations added, so I’ll list them here at the top:
Added Stations
11365563000 YAMOUSSOUKRO 6.90 -5.35 213 168U 50HIxxLA-9A15TROP. SEASONAL A 11365594000 SAN PEDRO 4.75 -6.65 30 0R -9FLFOCO 2A-9EQ. EVERGREEN C
Antarctic Deletion:
70089642000 DUMONT D'URVI -66.67 140.02 43 150R -9MVICCO 1x-9ANTARCTICA A
The Requiem List
Africa
10160355000 SKIKDA 36.93 6.95 7 18U 107HIxxCO 1x-9WARM DECIDUOUS C 10160403000 GUELMA 36.47 7.47 227 287S 47HIxxno-9x-9WARM CROPS C 10160430000 MILIANA 36.30 2.23 715 1167R -9MVDEno-9x-9WARM DECIDUOUS C 10160444000 BORDJ BOU ARR 36.07 4.77 928 1051U 57MVxxno-9x-9WARM FOR./FIELD C 10160445000 SETIF 36.18 5.42 1081 1060U 144MVxxno-9x-9WARM FOR./FIELD C 10160457000 MOSTAGANEM VI 35.88 0.12 137 157U 102HIxxCO 4A 2WARM CROPS B 10160468000 BATNA 35.55 6.18 1052 1015U 85MVxxno-9x-9WARM DECIDUOUS C 10160518000 BENI-SAF 35.30 -1.35 68 103R -9HIDECO 1x-9WARM CROPS B 10160535000 DJELFA 34.68 3.25 1144 1071U 51HIxxno-9x-9MED. GRAZING C 10160536000 SAIDA 34.87 0.15 750 802U 62MVxxno-9A 4MED. GRAZING C 10160540000 EL KHEITER 34.15 0.07 1000 1113R -9FLDEno-9x-9WARM DECIDUOUS B 10160549000 MECHERIA ALGERIA 33.60 -0.30 176 1501R -9MVDEno-9A-9MED. GRAZING A 10160555000 TOUGGOURT 33.12 6.13 85 106U 76FLxxno-9x-9HOT DESERT B 10160560000 AIN SEFRA 32.77 -0.60 1058 1811R -9MVDEno-9x-9WARM GRASS/SHRUBA 10160602000 BENI ABBES 30.13 -2.17 499 520R -9HIDEno-9A-9SAND DESERT C 10764910000 DOUALA OBS. 4.00 9.73 9 12U 458FLxxCO 5A 1MARSH, SWAMP C 10964655000 BRIA 6.53 21.98 584 587S 25FLxxno-9A 1TROP. SAVANNA A 11064700000 NDJAMENA 12.13 15.03 295 294U 179FLxxno-9A 2WARM GRASS/SHRUBC 11161968000 ILES GLORIEUS -11.58 47.28 4 0R -9FLxxCO 1A-9WATER A 11161970000 ILE JUAN DE N -17.05 42.70 10 0R -9FLxxCO 1A-9WATER A 11161972000 ILE EUROPA -22.32 40.33 13 0R -9FLxxCO 1A-9WATER A 11264400000 POINTE-NOIRE -4.82 11.90 17 7U 142FLxxCO 4A 2WATER B 11264401000 LOUBOMO -4.20 12.70 330 321S 20HIxxno-9A 1TROP. SAVANNA C 11264402000 MOUYONDZI -3.98 13.92 512 321R -9HIxxno-9x-9TROP. SAVANNA A 11264405000 SIBITI -3.68 13.35 531 481R -9HIxxno-9A-9TROP. SAVANNA A 11264450000 BRAZZAVILLE / -4.25 15.25 316 303U 299FLxxno-9A 2WARM CROPS C 11264454000 GAMBOMA -1.87 15.87 377 314R -9FLxxno-9A-9TROP. SEASONAL A 11365578000 ABIDJAN 5.25 -3.93 8 26U 686FLxxCO 1A 5COASTAL EDGES C 11365585000 ADIAKE 5.30 -3.30 39 25R -9FLxxCO 3x-9WARM FOR./FIELD A 11763331000 GONDAR 12.53 37.43 1966 2002S 39MVxxno-9A10TROP. MONTANE A 11763333000 COMBOLCHA 11.08 39.72 1916 1465U 50MVxxno-9A10HIGHLAND SHRUB B 11763402000 JIMMA 7.67 36.83 1676 1776S 40MVxxno-9A 2TROP. MONTANE B 11763403000 GORE 8.17 35.55 1974 1760R -9HIFOno-9A-9TROP. MONTANE A 11763450000 ADDIS ABABA 8.98 38.80 2324 2586U 1196MVxxno-9A 2WARM CROPS C 11763471000 DIRE DAWA 9.60 41.87 1146 1239U 64MVxxno-9A 2TROPICAL DRY FORC 12263612000 LODWAR 3.12 35.62 515 431R -9FLxxno-9A-9WARM GRASS/SHRUBA 12263740000 NAIROBI/KENYA -1.32 36.92 1624 1634U 509HIxxno-9A 2WARM FIELD WOODSC 12462002000 NALUT 31.87 10.98 621 570S 24HIxxno-9x-9WARM GRASS/SHRUBC 12462007000 ZUARA 32.88 12.08 3 5S 20FLxxCO 1x-9HIGHLAND SHRUB C 12462008000 YEFREN 32.08 12.55 691 575R -9HIDEno-9x-9WARM GRASS/SHRUBB 12462010000 TRIPOLI LIBYA 32.90 13.20 84 9U 550HIxxCO 3x-9MED. GRAZING C 12462012000 EL KHOMS 32.63 14.30 22 12S 17HIxxCO 2x-9WATER C 12462016000 MISURATA 32.42 15.05 32 5U 102FLxxCO 4x-9WARM GRASS/SHRUBC 12462019000 SIRTE 31.20 16.58 14 16S 23FLxxCO 1x-9WATER C 12462053000 BENINA 32.10 20.27 132 152U 287HIxxCO20A16WARM CROPS C 12462055000 AGEDABIA 30.72 20.17 7 6U 53FLxxCO25x-9WARM GRASS/SHRUBB 12462056000 SHAHAT 32.82 21.85 625 475S 17HIxxCO11x-9WARM CROPS C 12462059000 DERNA 32.78 22.58 26 138S 44HIxxCO 1x-9WATER B 12462103000 GHADAMES 30.13 9.50 347 273R -9HIDEno-9x-9WARM GRASS/SHRUBC 12462124000 SEBHA 27.02 14.45 432 424S 35FLxxno-9A 5SAND DESERT C 12462131000 HON 29.12 15.95 267 256R -9HIDEno-9A-9HOT DESERT A 12462161000 JALO 29.03 21.57 60 109R -9FLDEno-9x-9HOT DESERT A 12462176000 GIARABUB 29.75 24.53 -1 45R -9FLDEno-9x-9HOT DESERT B 12462271000 KUFRA 24.22 23.30 436 406R -9FLDEno-9A-9HOT DESERT C 12667693000 CHILEKA -15.68 34.97 767 802U 222MVxxno-9A10TROPICAL DRY FORB 12761214000 KIDAL 18.43 1.35 459 431R -9HIDEno-9A-9SUCCULENT THORNSA 12761270000 KITA 13.07 -9.47 334 381S 18HIxxno-9A 3WARM CROPS A 12761285000 KENIEBA 12.85 -11.23 132 306R -9HIFOno-9x-9TROP. SAVANNA A 12761297000 SIKASSO 11.35 -5.68 375 398S 47HIxxno-9A 2WARM CROPS B 12861421000 ATAR 20.52 -13.07 224 261S 16FLxxno-9x-9HOT DESERT B 12861437000 AKJOUJT 19.75 -14.37 120 134R -9FLDEno-9x-9HOT DESERT A 12861461000 BOUTILIMIT 17.53 -14.68 75 41R -9FLDEno-9x-9WARM GRASS/SHRUBA 13167215000 PORTO AMELIA -13.00 40.50 50 13R -9HIxxCO 2A-9WATER A 13167217000 VILA CABRAL -13.30 35.30 1365 1359S 10HIxxno-9x-9WARM CROPS A 13167237000 NAMPULA -15.10 39.28 441 435S 23HIxxno-9A 1TROP. SAVANNA C 13167261000 TETE -16.18 33.58 150 187R -9HIxxno-9x-9SUCCULENT THORNSA 13167283000 QUELIMANE -17.88 36.88 16 7S 11FLxxCO10x-9MARSH, SWAMP B 13167297000 BEIRA -19.80 34.90 16 6S 46FLxxCO 2A 5MARSH, SWAMP C 13167323000 INHAMBANE -23.87 35.38 15 22R -9FLxxCO 2A-9WARM CROPS B 13167341000 LOURENCO MARQUES/COUNTINHO -25.90 32.60 44 18U 755FLxxCO 7A 4MARSH, SWAMP C 13268312000 KEETMANSHOOP -26.53 18.12 1061 961S 10FLxxno-9x-9WARM GRASS/SHRUBA 13361090000 ZINDER 13.78 8.98 453 445U 58FLxxno-9A 1SUCCULENT THORNSA 13761679000 KAOLACK 14.13 -16.07 7 8U 107FLxxno-9x-9WARM CROPS B 14168262000 PRETORIA -25.73 28.18 1322 1377U 573HIxxno-9x-9WARM CROPS C 14168438000 KIMBERLEY -28.80 24.77 1200 1213U 105FLxxno-9A 3WARM GRASS/SHRUBC 14168588000 DURBAN (LOUIS -29.97 30.95 14 23U 975HIxxCO 2A 1WATER C 14168842000 PORT ELIZABET -33.98 25.60 61 63U 414HIxxCO 4A 1WATER C 14361997000 CROZET -46.43 51.87 143 0R -9HIxxCO 1x-9WATER A 14361998000 PORT-AUX-FRAN -49.35 70.25 30 173R -9HIxxCO 1x-9WATER A 14761901000 ST. HELENA IS. -16.00 -5.70 627 0R -9HIxxCO 1x-9WATER A 14862600000 WADI HALFA 21.92 31.32 126 192R -9FLDELA-9x-9WARM IRRIGATED A 14862640000 ABU HAMED 19.53 33.32 312 231R -9FLDEno-9x-9HOT DESERT A 14862641000 PORT SUDAN 19.58 37.22 2 16U 133FLxxCO 1x-9COASTAL EDGES C 14862650000 DONGOLA 19.17 30.48 226 229R -9FLDEno-9x-9WARM IRRIGATED C 14862660000 KARIMA 18.55 31.85 249 242S 13HIxxno-9x-9WARM IRRIGATED C 14862680000 ATBARA 17.70 33.97 345 288U 66FLxxno-9x-9WARM GRASS/SHRUBC 14862721000 KHARTOUM 15.60 32.55 380 239U 1334FLxxno-9A 1WARM IRRIGATED C 14862730000 KASSALA 15.47 36.40 500 518U 99HIxxno-9x-9WARM GRASS/SHRUBC 14862733000 HALFA EL GEDI 15.32 35.60 451 501R -9FLDEno-9x-9WARM IRRIGATED C 14862750000 ED DUEIM 14.00 32.33 378 261S 27FLxxno-9A 1WARM GRASS/SHRUBB 14862751000 WAD MEDANI 14.40 33.48 408 313U 107FLxxno-9x-9WARM GRASS/SHRUBC 14862752000 GEDAREF 14.03 35.40 599 544U 92FLxxno-9x-9SUCCULENT THORNSC 14862760000 EL FASHER 13.62 25.33 730 758U 52FLxxno-9A 1WARM GRASS/SHRUBB 14862762000 SENNAR 13.55 33.62 418 415S 10FLxxLA-9x-9SUCCULENT THORNSC 14862771000 EL OBEID 13.17 30.23 574 574U 90FLxxno-9A 1WARM GRASS/SHRUBC 14862772000 KOSTI 13.17 32.67 381 367U 57FLxxno-9x-9WARM GRASS/SHRUBC 14862795000 ABU NA'AMA 12.73 34.13 445 379R -9FLDEno-9x-9WARM GRASS/SHRUBA 14862805000 DAMAZINE 11.78 34.38 470 471R -9FLxxLA-9A-9SUCCULENT THORNSA 14862810000 KADUGLI 11.00 29.72 499 523S 18FLxxno-9x-9WARM GRASS/SHRUBC 14862880000 WAU 7.70 28.02 438 433U 53FLxxno-9x-9TROP. SAVANNA A 14963971000 MTWARA -10.27 40.18 113 74S 49HIxxCO 3x-9TROP. SEASONAL B 15061701000 BATHURST/YUNDUM 13.40 -16.70 26 6S 39FLxxCO 6A15COASTAL EDGES B 15165351000 DAPAON 10.87 0.25 330 279R -9HIxxno-9A-9WARM GRASS/SHRUBA 15165352000 MANGO 10.37 0.47 146 136R -9FLxxno-9A-9WARM GRASS/SHRUBA 15165355000 NIAMTOUGOU 9.77 1.10 343 340R -9HIxxno-9A-9WARM GRASS/SHRUBA 15165357000 KARA 9.55 1.17 341 308R -9HIxxno-9x-9WARM GRASS/SHRUBB 15165361000 SOKODE 8.98 1.15 387 419S 30HIxxno-9x-9TROPICAL DRY FORC 15165376000 ATAKPAME 7.58 1.12 402 427R -9HIxxno-9x-9TROP. SAVANNA A 15165380000 TABLIGBO 6.58 1.50 44 67R -9FLxxno-9x-9WARM FOR./FIELD A 15165387000 LOME 6.17 1.25 25 17U 148FLxxCO 5A 1WARM FOR./FIELD C 15567633000 MONGU -15.25 23.15 1053 1023R -9FLxxno-9A-9TROPICAL DRY FORB 15567663000 KABWE -14.45 28.47 1207 1195U 144HIxxno-9x-9SUCCULENT THORNSC 15567743000 LIVINGSTONE -17.82 25.82 986 970U 72FLxxno-9A 2SUCCULENT THORNSA 15761996000 ILE NOUVELLE-AMSTERDAM -37.80 77.50 28 0R -9HIxxCO 1x-9WATER A 15960010000 IZANA 28.30 -16.50 2368 1591R -9MTxxCO12x-9WATER B 16367005000 DZAOUDZI/PAMA -12.80 45.28 7 36R -9FLxxCO 1A-9WATER B 16561980000 SAINT-DENIS/G -20.88 55.52 25 239U 80HIxxCO 1A 1WATER C 16861976000 SERGE-FROLOW -15.88 54.52 13 0R -9FLxxCO 1A-9WATER A
Asia
20140948000 KABUL AIRPORT 34.55 69.22 1791 2290U 534MVxxno-9A 2WARM FIELD WOODSA 20140990000 KANDAHAR AIRP 31.50 65.85 1010 1008U 180HIxxno-9A15HOT DESERT A 20550527000 HAILAR 49.22 119.75 611 630U 120FLxxno-9A 1COOL FIELD/WOODSC 20550963000 TONGHE 45.97 128.73 110 477S 20HIxxno-9x-9COOL CROPS C 20551243000 KARAMAY 45.60 84.85 428 354R -9HIDEno-9x-9WARM GRASS/SHRUBC 20551644000 KUQA 41.72 82.95 1100 1300U 103HIxxno-9x-9WARM GRASS/SHRUBC 20551656000 KORLA 41.75 86.13 933 1189S 46FLxxno-9x-9SAND DESERT C 20552267000 EJIN QI 41.95 101.07 941 1220R -9HIDEno-9x-9HOT DESERT A 20552323000 MAZONG SHAN 41.80 97.03 1770 1906R -9HIDEno-9x-9HOT DESERT A 20552418000 DUNHUANG 40.15 94.68 1140 1066U 55FLxxno-9x-9COOL IRRIGATED B 20552495000 BAYAN MOD 40.75 104.50 1329 1220R -9HIDEno-9x-9HOT DESERT A 20552681000 MINQIN 38.63 103.08 1367 1520R -9FLDEno-9x-9SAND DESERT B 20552866000 XINING 36.62 101.77 2262 2376U 250MVxxno-9x-9WARM GRASS/SHRUBC 20553336000 HALIUT 41.57 108.52 1290 1317R -9HIDEno-9x-9HOT DESERT B 20553845000 YAN AN 36.60 109.50 959 1156R -9HIxxno-9A-9WARM GRASS/SHRUBC 20554026000 JARUD QI 44.57 120.90 266 300R -9FLDEno-9x-9COOL CROPS C 20554102000 XILIN HOT 43.95 116.07 991 1079S 40FLxxno-9x-9COOL GRASS/SHRUBC 20554161000 CHANGCHUN 43.90 125.22 238 283U 1500FLxxno-9x-9COOL FIELD/WOODSC 20554218000 CHIFENG 42.27 118.97 572 648U 90HIxxno-9x-9COOL CROPS C 20554662000 DALIAN 38.90 121.63 97 39U 1480HIxxCO 2x-9WATER C 20554823000 JINAN 36.68 116.98 58 60U 1500HIxxno-9x-9WARM FOR./FIELD C 20555228000 SHIQUANHE 32.50 80.08 4279 4597R -9MVxxno-9x-9WARM DECIDUOUS A 20555472000 XAINZA 30.95 88.63 4670 5205R -9MVxxno-9x-9TUNDRA A 20555591000 LHASA 29.67 91.13 3650 4813U 175MVxxno-9x-9SIBERIAN PARKS C 20556004000 TUOTUOHE 34.22 92.43 4535 4606R -9MVxxno-9x-9TUNDRA A 20556029000 YUSHU 33.02 97.02 3682 5078U 80MVxxno-9x-9TUNDRA A 20556046000 DARLAG 33.75 99.65 3968 4017R -9MVxxno-9x-9SIBERIAN PARKS A 20556079000 RUO'ERGAI 33.58 102.97 3441 3622R -9MVxxno-9x-9WARM CROPS A 20556106000 SOG XIAN 31.88 93.78 4024 5015R -9MVxxno-9x-9TUNDRA A 20556444000 DEQEN 28.50 98.90 3488 3349R -9MVxxno-9x-9TUNDRA A 20556964000 SIMAO 22.77 100.98 1303 1336R -9MVxxno-9x-9WARM DECIDUOUS B 20557127000 HANZHONG 33.07 107.03 509 611U 120MVxxno-9x-9WARM DECIDUOUS C 20557494000 WUHAN 30.62 114.13 23 60U 4250FLxxno-9x-9PADDYLANDS C 20557516000 CHONGQING 29.52 106.48 351 352U 3500HIxxno-9x-9PADDYLANDS C 20557816000 GUIYANG 26.58 106.72 1074 1289U 1500FLxxno-9x-9WARM GRASS/SHRUBC 20558027000 XUZHOU 34.28 117.15 42 60U 1500HIxxno-9A 1WARM CROPS C 20558238000 NANJING 32.00 118.80 12 100U 2000HIxxno-9x-9PADDYLANDS C 20558633000 QU XIAN 28.97 118.87 71 303U 60MVxxno-9x-9WARM MIXED C 20558666000 DACHEN DAO 28.45 121.88 84 0R -9HIxxCO 1x-9WATER A 20558847000 FUZHOU 26.08 119.28 85 199U 900HIxxCO30x-9PADDYLANDS C 20559211000 BAISE 23.90 106.60 242 268R -9HIxxno-9x-9PADDYLANDS C 20559948000 YAXIAN 18.23 109.52 7 48R -9HIxxCO 1A-9WATER C 20559981000 XISHA DAO 16.83 112.33 5 0R -9FLxxCO 1x-9WATER A 20647014000 CHUNGGANG 41.78 126.88 332 543R -9HIxxno-9x-9COOL MIXED A 20647016000 HYESAN 41.40 128.17 714 882S 20MVxxno-9x-9WARM FOR./FIELD C 20647025000 KIMCHAEK 40.67 129.20 19 272U 150HIxxCO 1x-9WARM GRASS/SHRUBC 20647035000 SINUIJU 40.10 124.38 7 30U 300HIxxno-9x-9WARM MIXED C 20647055000 WONSAN 39.18 127.43 36 29U 275HIxxCO 1x-9WARM GRASS/SHRUBB 20647058000 PYONGYANG 39.03 125.78 38 22U 1250FLxxno-9x-9WARM CROPS C 20647069000 HAEJU 38.03 125.70 81 93U 140MVxxCO 1x-9WARM CROPS C 20742071000 AMRITSAR 31.63 74.87 234 217U 458FLxxno-9x-9WARM IRRIGATED C 20742475000 ALLAHABAD/BAM 25.45 81.73 98 90U 513FLxxno-9A 4WARM CROPS C 20742587000 DALTONGANJ 24.05 84.07 221 279S 43HIxxno-9x-9WARM CROPS C 20840706000 TABRIZ 38.08 46.28 1361 1479U 599MVxxno-9x-9WARM GRASS/SHRUBC 20840712000 ORUMIEH 37.53 45.08 1312 1402U 164MVxxno-9x-9HOT DESERT C 20840729000 ZANJAN 36.68 48.48 1663 1752U 100MVxxno-9x-9HIGHLAND SHRUB C 20840731000 GHAZVIN 36.25 50.00 1278 1284U 139FLxxno-9x-9COOL FOR./FIELD C 20840738000 GORGAN 36.82 54.47 155 280U 88MVxxno-9x-9WARM MIXED C 20840745000 MASHHAD 36.27 59.63 980 1035U 670MVxxno-9x-9HIGHLAND SHRUB C 20840747000 SANANDAJ 35.33 47.00 1373 1650U 96MVxxno-9x-9WARM GRASS/SHRUBC 20840754000 TEHRAN-MEHRAB 35.68 51.35 1191 1230U 4496MVxxno-9A 1HIGHLAND SHRUB C 20840757000 SEMNAN 35.55 53.38 1171 1406S 31MVxxno-9x-9HIGHLAND SHRUB C 20840766000 KRMANSHAH 34.27 47.12 1322 1482U 291MVxxno-9x-9WARM CROPS B 20840769000 ARAK 34.10 49.40 1720 1941U 115MVxxno-9x-9WARM GRASS/SHRUBB 20840798000 SHAHRE-KORD 32.33 50.85 1991 2436S 24MVxxno-9x-9WARM FIELD WOODSC 20840800000 ESFAHAN 32.47 51.72 1550 1620U 672HIxxno-9A 1HOT DESERT B 20840809000 BIRJAND 32.87 59.20 1491 1528S 26MVxxno-9x-9WARM FIELD WOODSC 20840841000 KERMAN 30.25 56.97 1754 2096U 140MVxxno-9A 5COOL GRASS/SHRUBC 20840848000 SHIRAZ 29.53 52.58 1491 1909U 416MVxxno-9A 3HIGHLAND SHRUB C 20840856000 ZAHEDAN 29.47 60.88 1370 1580U 93HIxxno-9x-9WARM FIELD WOODSC 20840875000 BANDARABBASS 27.22 56.37 10 149U 89FLxxCO 3A 3WARM GRASS/SHRUBC 21047582000 AKITA 39.72 140.10 21 12U 261FLxxCO 3x-9PADDYLANDS C 21128952000 KUSTANAI 53.22 63.62 156 180U 165FLxxno-9x-9COOL CROPS C 21135746000 ARALSKOE MORE 46.78 61.65 62 33S 38FLxxLA-9x-9WARM GRASS/SHRUBC 21135925000 SAM 45.40 56.12 82 117R -9FLDEno-9x-9HOT DESERT A 21136859000 PANFILOV 44.17 80.07 645 953S 19MVxxno-9x-9WARM GRASS/SHRUBC 21138001000 FORT SEVCENKO 44.55 50.25 -25 1S 12FLxxCO 1x-9WATER B 21448930000 LUANG-PRABANG 19.88 102.13 305 673R -9MVxxno-9A-9TROP. SEASONAL B 21544203000 RINCHINLHUMBE 51.12 99.67 1583 1720R -9MVxxno-9x-9SOUTH. TAIGA C 21544207000 HATGAL 50.43 100.15 1668 1816R -9MVxxLA-9x-9SOUTH. TAIGA A 21544213000 BARUUNTURUUN 49.65 94.40 1232 1318R -9MVDEno-9x-9TUNDRA A 21544214000 UIGI 48.93 89.93 1715 2256S 15MVxxno-9x-9HOT DESERT A 21544215000 OMNO-GOBI 49.02 91.72 1590 1903R -9MVxxLA-9x-9COOL DESERT A 21544218000 HOVD 48.02 91.57 1405 1574S 25MVxxno-9x-9HOT DESERT A 21544225000 TOSONTSENGEL 48.73 98.28 1723 2062R -9MVxxno-9x-9COOL DESERT A 21544230000 TARIALAN 49.57 102.00 1235 1317R -9MVxxno-9x-9SOUTH. TAIGA A 21544231000 MUREN 49.57 100.17 1283 1659S 20MVxxno-9x-9COOL DESERT A 21544232000 HUTAG 49.38 102.70 938 1280R -9MVxxno-9x-9COOL DESERT A 21544237000 ERDENEMANDAL 48.53 101.38 1510 1801R -9MVxxno-9x-9COOL DESERT A 21544239000 BULGAN 48.80 103.55 1208 1484S 15HIxxno-9x-9COOL GRASS/SHRUBA 21544241000 BAYAN-GOL, SELENGE 48.90 106.10 807 914R -9HIxxno-9x-9COOL GRASS/SHRUBA 21544259000 CHOIBALSAN 48.08 114.55 747 910S 30FLxxno-9x-9COOL GRASS/SHRUBB 21544272000 ULIASTAI 47.75 96.85 1759 2525S 15MVxxno-9x-9TUNDRA A 21544277000 ALTAI 46.40 96.25 2181 2716S 14MVxxno-9x-9WARM GRASS/SHRUBA 21544282000 TSETSERLEG 47.45 101.47 1691 2290S 28HIxxno-9x-9COOL DESERT A 21544284000 GAIUUT 46.70 100.13 2126 2135S 10MVxxno-9x-9TUNDRA A 21544285000 HUJIRT 46.90 102.77 1662 1898R -9HIDEno-9x-9COOL GRASS/SHRUBA 21544287000 BAYANHONGOR 46.13 100.68 1859 1980S 10MVxxno-9x-9COOL DESERT A 21544288000 ARVAIHEER 46.27 102.78 1813 1819S 12HIxxno-9x-9COOL GRASS/SHRUBA 21544292000 DAUUNMOD, CENTRAL 47.80 106.80 -999 1520S 12HIxxno-9x-9COOL GRASS/SHRUBA 21544294000 MAANTI 47.30 107.48 1430 1520R -9FLDEno-9x-9COOL GRASS/SHRUBA 21544298000 CHOIR 46.45 108.22 1286 1520R -9FLDEno-9x-9COOL GRASS/SHRUBA 21544302000 BAYAN-OVOO 47.78 112.12 926 996R -9FLDEno-9x-9COOL GRASS/SHRUBA 21544304000 UNDERKHAAN 47.32 110.63 1033 1220S 14FLxxno-9x-9COOL GRASS/SHRUBC 21544305000 BARUUN-URT 46.68 113.28 981 910S 12FLxxno-9x-9COOL GRASS/SHRUBA 21544336000 SAIKHAN-OVOO 45.45 103.90 1316 1370R -9FLDEno-9x-9WARM GRASS/SHRUBA 21544341000 MANDALGOVI 45.77 106.28 1393 1228S 10FLxxno-9x-9WARM GRASS/SHRUBC 21544347000 TSOGT-OVOO 44.42 105.32 1298 1271R -9FLDEno-9x-9WARM GRASS/SHRUBA 21544352000 BAYANDELGER 45.73 112.37 1101 1064R -9FLDEno-9x-9COOL GRASS/SHRUBA 21544354000 Sainshand 44.90 110.10 -999 926S 14FLxxno-9x-9WARM GRASS/SHRUBA 21544358000 ZAMYN-UUD 43.73 111.90 964 929R -9FLDEno-9x-9COOL GRASS/SHRUBB 21544373000 DALANZADGAD 43.58 104.42 1465 1556S 10MVxxno-9A 1WARM GRASS/SHRUBA 21744454000 KATHMANDU AIR 27.70 85.37 1337 1538U 354MVxxno-9A 2WARM FIELD WOODSC 21941560000 PARACHINAR 33.87 70.08 1726 2198R -9MVxxno-9A-9COOL GRASS/SHRUBA 22041170000 DOHA INTERNAT 25.25 51.57 10 10U 250FLxxCO 3A 1WATER C 22223711000 TROICKO-PECER 62.70 56.20 139 106R -9FLxxno-9A-9MAIN TAIGA C 22223921000 IVDEL' 60.68 60.45 95 190S 15HIxxno-9x-9BOGS, BOG WOODS C 22225744000 KAMENSKOE 62.43 166.08 10 256R -9MVxxno-9x-9WOODED TUNDRA A 22228138000 BISER 58.52 58.85 463 388R -9MTxxno-9x-9COOL MIXED B 22228434000 KRASNOUFIMSK 56.65 57.78 206 240S 40HIxxno-9x-9COOL GRASS/SHRUBC 22228552000 SADRINSK 56.07 63.65 89 121U 82FLxxno-9x-9COOL CROPS C 22229807000 IRTYSSK 53.35 75.45 94 120R -9FLxxno-9x-9COOL IRRIGATED C 22232411000 ICA 55.58 155.58 6 3R -9FLxxCO 1x-9SIBERIAN PARKS A 22340356000 TURAIF 31.68 38.73 852 816R -9FLDEno-9A-9HOT DESERT C 22340405000 GASSIM 26.30 43.77 650 582U 70FLxxno-9A15SAND DESERT C 22340438000 RIYADH 24.72 46.73 620 696U 1380FLxxno-9A 1WARM IRRIGATED C 22340439000 YENBO 24.02 38.22 11 71S 25HIxxCO 7A 3HOT DESERT C 22443424000 PUTTALAM 8.03 79.83 2 3S 18FLxxCO 1x-9WATER B 22443466000 COLOMBO 6.90 79.87 7 9U 852FLxxCO 1x-9WATER C 22443473000 NUWARA ELIYA 6.97 80.77 1880 1543S 16MVxxno-9x-9WARM FOR./FIELD B 22443497000 HAMBANTOTA 6.12 81.13 20 42S 11FLxxCO 1x-9WARM GRASS/SHRUBA 22848462000 ARANYAPRATHET 13.70 102.58 49 61R -9HIFOno-9x-9TROPICAL DRY FORA 23041196000 SHARJAH INTER 25.33 55.52 33 30U 266FLxxCO10A 5WARM GRASS/SHRUBC 23248820000 HA NOI 21.02 105.80 6 45U 2571FLxxno-9x-9PADDYLANDS C 23248826000 PHU LIEN 20.80 106.63 119 60U 1279FLxxCO14x-9PADDYLANDS B 23248855000 DA NANG 16.03 108.18 7 233U 492MVxxCO 2A 1WATER B 23248877000 NHA TRANG 12.25 109.20 10 20U 216MVxxCO 1A 1WATER C
South America
30187934000 RIO GRANDE B. -53.80 -67.75 22 32S 13FLxxCO 3A 2WATER B 30382397000 FORTALEZA -3.77 -38.60 26 0U 648FLxxCO 1x-9WARM CROPS C 30382578000 TERESINA -5.08 -42.82 74 112U 339FLxxno-9A 1WARM CROPS C 30382861000 CONCEICAO DO -8.25 -49.28 157 157R -9HIxxno-9A-9WARM GRASS/SHRUBC 30383096000 ARACAJU -10.92 -37.05 5 29U 288FLxxCO 2x-9WARM FOR./FIELD C 30383229000 SALVADOR -13.02 -38.52 51 3U 1496HIxxCO 2x-9WATER C 30383361000 CUIABA -15.55 -56.12 151 170U 167HIxxno-9x-9MARSH, SWAMP C 30383552000 CORUMBA -19.08 -57.50 130 171U 66FLxxno-9x-9TROP. SAVANNA A 30383618000 TRES LAGOAS -20.78 -51.70 313 353S 45HIxxLA-9x-9WARM FIELD WOODSC 30383702000 PONTA PORA -22.53 -55.73 650 629S 20HIxxno-9A 2TROP. SEASONAL C 30489056000 CENTRO MET.AN -62.42 -58.88 10 0R -9HIICCO 1x-9ANTARCTICA A 30886033000 BAHIA NEGRA -20.22 -58.17 96 86R -9FLMAno-9A-9SEMIARID WOODS A 30886065000 PRATS-GIL -22.70 -61.50 220 224R -9FLxxno-9A-9SUCCULENT THORNSA 30886068000 MARISCAL -22.02 -60.60 181 189R -9FLxxno-9A-9SUCCULENT THORNSC 30886086000 PUERTO CASADO -22.28 -57.87 87 80R -9FLMAno-9A-9TROPICAL DRY FORA 30886097000 PEDRO JUAN CA -22.58 -55.65 662 631S 20HIxxno-9A 2TROP. SEASONAL A 30886134000 CONCEPCION -23.42 -57.30 74 85S 19FLxxno-9x-9TROPICAL DRY FORA 30886218000 ASUNCION/AERO -25.27 -57.63 101 90U 388FLxxno-9A 5TROPICAL DRY FORC 30886233000 SAN JUAN BAUTISTA/MISIONES -25.80 -56.30 155 233R -9HIFOno-9x-9TROP. SEASONAL A 30886255000 PILAR -26.85 -58.32 56 60S 15FLxxno-9A 1MARSH, SWAMP B 30886260000 SAN JUAN BAUT -26.67 -57.15 126 90R -9HIxxno-9x-9TROPICAL DRY FORB 30886297000 ENCARNACION -27.32 -55.83 91 91S 23FLxxno-9A 6WARM FIELD WOODSC 30984370000 TUMBES -3.55 -80.40 27 35S 48FLxxCO 5A 5WARM GRASS/SHRUBA 30984377000 IQUITOS -3.75 -73.25 126 90R -9FLFOno-9x-9EQ. EVERGREEN A 30984401000 PIURA -5.18 -80.60 55 67U 186HIxxno-9A 1HOT DESERT C 30984452000 CHICLAYO -6.78 -79.83 34 43U 280FLxxCO15A 1WARM IRRIGATED C 30984455000 TARAPOTO -6.45 -76.38 282 995R -9HIFOno-9A-9EQ. EVERGREEN B 30984501000 TRUJILLO -8.10 -79.03 30 231U 355MVxxCO 6x-9WATER C 30984515000 PUCALLPA -8.42 -74.60 149 180U 92HIxxLA-9A 3EQ. EVERGREEN B 30984628000 LIMA-CALLAO/A -12.00 -77.12 13 20U 376MVxxCO 2A 1WATER C 30984686000 CUZCO -13.55 -71.98 3249 3693U 181MVxxno-9x-9TUNDRA B 30984691000 PISCO -13.75 -76.28 7 5U 53FLxxCO 1A 1WATER B 30984735000 JULIACA -15.48 -70.15 3827 3833U 78MVxxno-9A 1COOL CROPS C 30984782000 TACNA -18.07 -70.30 469 385U 93MVxxCO30A 2HOT DESERT B 31281225000 ZANDERIJ 5.45 -55.20 15 30R -9FLxxno-9A-9COOL CROPS B 31386330000 ARTIGAS -30.38 -56.50 120 140S 29FLxxno-9A 2WARM GRASS/SHRUBB 31386350000 RIVERA -30.88 -55.53 241 254U 50FLxxno-9x-9WARM GRASS/SHRUBC 31386360000 SALTO -31.38 -57.95 33 52U 73FLxxno-9x-9WARM GRASS/SHRUBC 31386430000 PAYSANDU -32.33 -58.03 61 58U 62FLxxno-9x-9WARM GRASS/SHRUBB 31386440000 MELO -32.37 -54.22 100 142S 38HIxxno-9A 5WARM GRASS/SHRUBA 31386560000 COLONIA -34.45 -57.83 22 0S 17FLxxCO 2x-9WATER B 31386565000 ROCHA -34.48 -54.30 18 46S 22HIxxCO20A 1COASTAL EDGES C 31386580000 CARRASCO -34.83 -56.00 32 16U 1173FLxxCO 3A 2WARM CROPS C 31480403000 CORO 11.42 -69.68 17 19U 69HIxxCO 6A 1TROPICAL DRY FORC 31480410000 BARQUISIMETO 10.07 -69.32 614 551U 331HIxxno-9x-9WARM GRASS/SHRUBC 31480413000 MARACAY - B.A 10.25 -67.65 437 640U 255MVxxLA-9A 1WARM GRASS/SHRUBC 31480415000 CARACAS/MAIQU 10.60 -66.98 48 239U 1035MVxxCO 1A10WATER C 31480416000 CARACAS/LA CARLOTA 10.50 -66.90 865 1135U 1035MVxxCO12x-9WARM CROPS C 31480419000 BARCELONA 10.12 -64.68 7 62U 78HIxxCO 3A 1WATER C 31480423000 LA GUIRIA VENEZUE 10.58 -62.30 8 136S 15HIxxCO 1A 1COASTAL EDGES C 31480435000 MATURIN 9.75 -63.18 66 70U 98FLxxno-9x-9WARM GRASS/SHRUBC 31480438000 MERIDA 8.60 -71.18 1498 2555U 74MVxxno-9x-9WARM GRASS/SHRUBC 31480444000 CIUDAD BOLIVA 8.15 -63.55 48 62U 104FLxxno-9A 1TROP. SAVANNA C 31480447000 SAN ANTONIO D 7.85 -72.45 378 474U 220MVxxno-9A 2TROP. MONTANE C 31480450000 SAN FERNANDO 7.90 -67.42 48 55S 39FLxxno-9A 5WARM GRASS/SHRUBC 31480453000 TUMEREMO 7.30 -61.45 181 183R -9FLxxno-9A-9WARM GRASS/SHRUBA 31480457000 PUERTO AYACUC 5.60 -67.50 74 162S 10FLxxno-9A10TROP. SAVANNA A 31480462000 SANTA ELENA D 4.60 -61.12 907 934R -9HIxxno-9x-9TROP. MONTANE C 31581401000 SAINT-LAURENT 5.50 -54.03 9 34R -9FLxxCO30x-9EQ. EVERGREEN C 31581405000 CAYENNE/ROCHA 4.83 -52.37 9 109S 37HIxxCO10A10MARSH, SWAMP B 31581408000 SAINT GEORGES 3.88 -51.80 7 46R -9FLxxno-9x-9EQ. EVERGREEN A 31581415000 MARIPASOULA 3.63 -54.03 106 268R -9HIxxno-9A-9EQ. EVERGREEN A
North America
40278583000 BELIZE/PHILLI 17.53 -88.30 5 16U 51FLxxCO 3A10TROP. SEASONAL A 40578762000 JUAN SANTAMAR 10.00 -84.22 939 1060S 33MVxxno-9A 2TROP. SEASONAL C 40578767000 PUERTO LIMON 10.00 -83.05 3 60S 30FLxxCO 1x-9TROP. SEASONAL C 40678367000 GUANTANAMO,OR 19.90 -75.13 23 3R -9HIxxCO 1A-9WATER C 41278705000 LA CEIBA (AIR 15.73 -86.87 26 240S 39MVxxCO 2A 5WARM FOR./FIELD B 41278708000 LA MESA 15.45 -87.93 31 43U 151MVxxno-9A10WARM DECIDUOUS C 41278720000 TEGUCIGALPA 14.05 -87.22 1007 1047U 305MVxxno-9A 2WARM FOR./FIELD C 41476160000 HERMOSILLO,SO 29.07 -110.95 211 225U 233HIxxno-9x-9WARM GRASS/SHRUBC 41476220000 TEMOSACHIC,CH 28.95 -107.83 1870 1944R -9MVxxno-9x-9WARM DECIDUOUS B 41476225000 UNIV. DE CHIH 28.63 -106.08 1435 1528U 327MVxxno-9x-9WARM GRASS/SHRUBC 41476243000 PIEDRAS NEGRA 28.70 -100.52 250 227S 21FLxxno-9A 1WARM GRASS/SHRUBC 41476311000 CHOIX,SIN. 26.72 -108.28 238 403R -9HIxxno-9x-9TROP. SAVANNA A 41476342000 MONCLOVA,COAH 26.88 -101.42 615 768U 78MVxxno-9x-9SUCCULENT THORNSC 41476373000 TEPEHUANES,DG 25.35 -105.75 1810 2061R -9MVxxno-9x-9WARM DECIDUOUS B 41476382000 TORREON,COAH. 25.53 -103.45 1124 1339U 244HIxxno-9x-9WARM GRASS/SHRUBC 41476390000 SALTILLO,COAH 25.45 -100.98 1790 1594U 201MVxxno-9x-9SUCCULENT THORNSC 41476393000 MONTERREY,N.L 25.87 -100.20 512 548U 1923MVxxno-9x-9WARM IRRIGATED C 41476405000 LA PAZ, B.C.S 24.27 -110.42 18 71S 46HIxxCO 3x-9WATER A 41476458000 MAZATLAN 23.20 -105.40 3 1642U 147FLxxCO 1x-9TROP. SAVANNA A 41476525000 ZACATECAS,ZAC 22.78 -102.57 2612 2421U 50HIxxno-9x-9WARM DECIDUOUS C 41476548000 TAMPICO, TAMP 22.22 -97.85 9 32U 212FLxxCO 5x-9COASTAL EDGES C 41476556000 TEPIC,NAY. 21.52 -104.90 922 927U 109MVxxCO30x-9WARM CROPS C 41476577000 GUANAJUATO,GT 21.02 -101.25 1999 2244S 37HIxxno-9x-9WARM FIELD WOODSC 41476581000 RIO VERDE,S.L 21.85 -100.00 990 1038S 17HIxxno-9x-9COOL DESERT A 41476632000 PACHUCA,HGO. 20.13 -98.73 2417 2508U 84MVxxno-9x-9WARM CROPS C 41476640000 TUXPAN.VER. 20.95 -97.40 28 27S 34FLxxCO 7x-9WARM CROPS C 41476644000 AEROP.INTERNA 20.98 -89.65 9 10U 234FLxxno-9A 2WARM CROPS C 41476647000 VALLADOLID,YU 20.70 -88.22 22 15S 15FLxxno-9x-9TROP. SAVANNA C 41476654000 MANZANILLO,CO 19.05 -104.33 3 30S 21HIxxCO 1x-9TROPICAL DRY FORC 41476662000 ZAMORA,MICH. 19.98 -102.32 1562 1733R -9MVxxno-9A-9WARM CROPS C 41476665000 MORELIA,MICH. 19.70 -101.18 1913 1979U 199MVxxno-9x-9WARM FIELD WOODSC 41476680000 MEXICO (CENTR 19.40 -99.20 2303 2307U13994MVxxno-9x-9WARM CROPS C 41476683000 TLAXCALA,TLAX 19.32 -98.23 2248 2342S 10HIxxno-9x-9TROP. MONTANE C 41476685000 PUEBLA,PUE. 19.05 -98.17 2179 2151U 466MVxxno-9x-9TROP. MONTANE C 41476687000 JALAPA,VER. 19.53 -96.92 1389 1423U 161MVxxno-9x-9WARM CROPS C 41476692000 HACIENDA YLAN 19.15 -96.12 13 6U 256FLxxCO 1x-9TROP. SEASONAL C 41476695000 CAMPECHE,CAMP 19.85 -90.55 5 8U 70FLxxCO 1x-9WATER C 41476726000 CUERNAVACA,MO 18.88 -99.23 1618 1720U 240MVxxno-9x-9WARM CROPS C 41476741000 COATZACOALCOS 18.15 -94.42 23 3U 70FLxxCO 1x-9WATER C 41476750000 CHETUMAL,Q.RO 18.48 -88.30 9 3S 24FLxxCO 1x-9TROP. SEASONAL C 41476775000 OAXACA,OAX. 17.07 -96.72 1550 1858U 115MVxxno-9x-9TROP. SAVANNA C 41476805000 ACAPULCO,GRO. 16.83 -99.93 13 113U 309MVxxCO 1x-9COASTAL EDGES C 41476845000 SN. CRISTOBAL 16.73 -92.63 2276 2336S 26MVxxno-9x-9TROP. SEASONAL C 41476903000 TAPACHULA, CH 14.92 -92.27 118 281U 60MVxxCO20A 3TROPICAL DRY FORC 41578741000 MANAGUA, NICARAGUA 12.10 -86.20 56 107U 405HIxxLA-9A 5WARM FIELD WOODSC 42572259000 DALLAS-FORT W 32.90 -97.03 182 161U 4037FLxxno-9A 5WARM FIELD WOODSC 42572597000 MEDFORD/MEDFO 42.37 -122.87 405 415S 47MVxxno-9A 2WARM FOR./FIELD C 42978384000 OWEN ROBERTS 19.28 -81.35 3 0R -9FLxxCO 1A-9WATER C 43104220000 EGEDESMINDE 68.70 -52.75 41 20R -9HIxxCO 1x-9WATER A 43104250000 GODTHAB NUUK 64.17 -51.75 70 0R -9MVxxCO 1A-9TUNDRA B 43104312000 NORD ADS 81.60 -16.67 34 13R -9HIxxCO 1x-9ICE A 43104320000 DANMARKSHAVN 76.77 -18.67 12 265R -9FLxxCO 1x-9WATER A 43104360000 ANGMAGSSALIK 65.60 -37.63 52 275R -9MVxxCO 1x-9WATER A 43104390000 PRINS CHRISTI 60.05 -43.17 74 0R -9HIxxCO 1x-9TUNDRA A 43278897000 LE RAIZET,GUA 16.27 -61.52 11 36S 25HIxxCO 2A 3WATER C 43378925000 LAMENTIN/MARTINIQUE/FT DE 14.60 -61.10 144 64U 98HIxxCO 1x-9WATER C 43478866000 JULIANA AIRPO 18.05 -63.12 9 24R -9HIxxCO 1A-9WATER C 43478988000 HATO AIRPORT, 12.20 -68.97 67 0U 95FLxxCO 1A10WATER C 43871805000 SAINT-PIERRE 46.77 -56.17 5 10R -9HIxxCO 1A-9WATER B
Pacific Region
50194259000 BURKETOWN -17.73 139.53 8 7R -9FLxxCO30x-9WARM FIELD WOODSA 50194968000 LAUNCESTON AI -41.53 147.20 178 146S 31HIxxno-9A 8COOL FIELD/WOODSB 50291652000 UNDU POINT -16.13 -179.98 63 0R -9HIxxCO 1x-9WATER A 50291680000 NANDI -17.75 177.45 18 65R -9HIxxCO 1A-9TROP. MONTANE C 50291683000 NAUSORI -18.05 178.57 7 88U 64HIxxCO 8A20WATER B 50291699000 ONO-I-LAU -20.67 -178.72 28 0R -9HIxxCO 1A-9WATER A 50396109000 PAKANBARU/ 0.47 101.45 31 83U 186FLxxno-9A 3EQ. EVERGREEN C 50396633000 BALIKPAPAN/SE -1.27 116.90 3 19U 281FLxxCO 1A 1EQ. EVERGREEN C 50396745000 JAKARTA/OBSER -6.18 106.83 8 27U 6503FLxxCO 6x-9PADDYLANDS C 50396797000 TEGAL -6.85 109.15 10 0U 132FLxxCO 1x-9PADDYLANDS C 50396925000 SANGKAPURA -5.85 112.63 3 0R -9HIxxCO 1x-9WATER A 50396973000 KALIANGET(MAD -7.05 113.97 3 70R -9FLxxCO 1x-9COASTAL EDGES A 50397048000 GORONTALO/JAL 0.52 123.07 2 75U 98MVxxCO 3x-9WATER B 50397182000 UJANG PANDANG -5.07 119.55 -999 30U 709HIxxCO 7A15WARM CROPS C 50397240000 AMPENAN/SELAP -8.53 116.07 3 35S 47MVxxCO 2A 3WARM FOR./FIELD B 50397796000 KOKONAO/TIMUK -4.72 136.43 3 0R -9FLMACO 1x-9WATER A 50548674000 MERSING 2.45 103.83 45 0S 18FLxxCO 1x-9WARM FOR./FIELD B 50998755000 HINATUAN 8.37 126.33 3 50R -9FLxxCO 1x-9TROP. SEASONAL A 51891643000 FUNAFUTI -8.52 179.22 2 0R -9FLxxCO 1A-9WATER A 52091554000 PEKOA -15.52 167.22 56 286R -9HIxxCO 5A-9WATER A 52091568000 ANEITYUM -20.23 169.77 7 148R -9HIxxCO 1A-9WATER A 52191765000 PAGO PAGO/INT -14.33 -170.72 3 0R -9HIxxCO 1A-9WATER C 52791334000 TRUK, 7.47 151.85 2 0R -9HIxxCO 1A-9WATER C 52791348000 PONAPE, 6.97 158.22 46 0R -9HIxxCO 1A-9WATER C 52791413000 YAP, CAROLINE 9.48 138.08 17 0R -9HIxxCO 1A-9WATER A 52891925000 ATUONA -9.80 -139.03 52 0R -9HIxxCO 4A-9WATER A 52891938000 TAHITI-FAAA -17.55 -149.62 2 0S 23MVxxCO 1A 2WATER C 52891943000 TAKAROA -14.48 -145.03 3 0R -9FLxxCO 1x-9WATER A 52891945000 HEREHERETUE -19.87 -145.00 3 0R -9FLxxCO 1x-9WATER A 52891948000 TOTEGEGIE, GAMBIER IS. -23.10 -134.90 3 0R -9FLxxCO 1A-9WATER A 52891954000 TUBUAI -23.35 -149.48 3 0R -9HIxxCO 1A-9WATER A 52891958000 RAPA -27.62 -144.33 2 0R -9HIxxCO 1x-9WATER A 53191366000 KWAJALEIN/BUC 8.73 167.73 8 0R -9FLxxCO 1A-9WATER B 53191376000 MAJURO/MARSHA 7.08 171.38 3 0R -9FLxxCO 1x-9WATER B 53291577000 KOUMAC -20.57 164.28 18 42R -9MVxxCO 1x-9WATER A 53291592000 NOUMEA -22.27 166.45 72 0U 56HIxxCO 2A 1WATER C 53691408000 KOROR, PALAU 7.33 134.48 33 0R -9HIxxCO 1A-9WATER B 53991245000 WAKE ISLAND A 19.28 166.65 4 0R -9FLxxCO 1A-9WATER A 54091753000 HIHIFO -13.23 -176.17 27 0R -9HIxxCO 2A-9WATER A
Europe
60237789000 YEREVAN 40.13 44.47 907 1067U 1019MVxxno-9A 1WARM GRASS/SHRUBC 61111464000 MILESOVKA 50.55 13.93 -999 409R -9MVxxno-9x-9COOL CROPS A 61111518000 PRAHA/RUZYNE 50.10 14.25 365 322U 1161HIxxno-9A 3COOL FOR./FIELD C 61111520000 PRAHA-LIBUS 50.02 14.45 304 309U 1161HIxxno-9x-9COOL CROPS C 61111723000 BRNO/TURANY 49.15 16.70 246 302U 336HIxxno-9A 4COOL FOR./FIELD B 61111782000 OSTRAVA/MOSNO 49.68 18.12 256 278U 294HIxxno-9A15COOL CONIFER A 61206030000 ALBORG 57.10 9.87 13 10U 155FLxxCO30A 5WARM CROPS C 61206186000 KOBENHAVN/ 55.68 12.55 9 5U 1328FLxxCO 1x-9WATER C 61206190000 RONNE 55.07 14.75 16 81S 15FLxxCO 1A 3WATER A 61507015000 LILLE 50.57 3.10 52 33U 171FLxxno-9x-9WARM CROPS C 61507037000 ROUEN 49.38 1.18 157 131U 114HIxxno-9A 3WARM CROPS C 61507110000 BREST 48.45 -4.42 103 78U 164FLxxCO 7A 3WARM CROPS C 61507190000 STRASBOURG 48.55 7.63 154 170U 252FLxxno-9A 3WARM DECIDUOUS C 61507222000 NANTES 47.17 -1.60 27 51U 253FLxxno-9A 3WARM CROPS C 61507255000 BOURGES 47.07 2.37 166 152U 75HIxxno-9A 1WARM CROPS C 61507280000 DIJON 47.27 5.08 227 241U 150HIxxno-9A 4WARM FOR./FIELD C 61507434000 LIMOGES 45.87 1.18 402 335U 136HIxxno-9A 5WARM CROPS C 61507460000 CLERMONT-FERR 45.78 3.17 330 473U 153MVxxno-9x-9WARM CROPS C 61507510000 BORDEAUX/MERI 44.83 -0.70 61 44U 220FLxxCO30A 3WARM DECIDUOUS C 61507560000 MONT AIGOUAL 44.12 3.58 1565 1019R -9MTxxno-9x-9MED. GRAZING A 61507630000 TOULOUSE/BLAG 43.63 1.37 153 160U 371FLxxno-9A 3WARM GRASS/SHRUBC 61507643000 MONTPELLIER 43.58 3.97 6 38U 178HIxxCO 8x-9WARM CROPS C 61507650000 MARSEILLE/MARIGNANE FRANCE 43.30 5.40 8 95U 901HIxxCO10A10WATER C 61507690000 NICE 43.65 7.20 10 142U 331MVxxCO 1A 5WARM CROPS C 61507747000 PERPIGNAN 42.73 2.87 48 45U 101FLxxCO12x-9WARM CROPS C 61507761000 AJACCIO 41.92 8.80 9 80S 47MVxxCO 1A 3MED. GRAZING C 61710020000 LIST/SYLT 55.02 8.42 29 0R -9FLxxCO 1x-9WATER A 61710348000 BRAUNSCHWEIG 52.30 10.45 88 74U 269FLxxno-9x-9WARM CROPS C 61710381000 BERLIN-DAHLEM 52.47 13.30 58 41U 3021FLxxno-9x-9WARM CONIFER C 61710384000 BERLIN-TEMPEL 52.47 13.40 49 41U 3021FLxxno-9A 1WARM CONIFER C 61710410000 ESSEN 51.40 6.97 161 113U 7452HIxxno-9A 3WARM FIELD WOODSC 61710444000 GOETTINGEN 51.50 9.95 171 214U 124HIxxno-9x-9WARM DECIDUOUS A 61710739000 STUTTGART/ 48.83 9.20 311 301U 600HIxxno-9x-9WARM CROPS C 61816622000 THESSALONIKI 40.52 22.97 4 107U 482HIxxCO 1A 6MED. GRAZING C 61816641000 KERKYRA (AIRP 39.62 19.92 4 39S 29HIxxCO 2A 1WATER C 61816648000 LARISSA 39.63 22.42 74 101U 72HIxxno-9x-9MED. GRAZING C 61816714000 ATHINAI/OBSER 37.97 23.72 107 100U 2567HIxxCO 6x-9WARM CROPS C 61816716000 ATHINAI (AIRP 37.90 23.73 15 19U 2567HIxxCO 1A 2WARM CROPS C 61816723000 SAMOS (AIRPOR 37.70 26.92 7 73R -9HIxxCO 1A-9WARM CROPS B 61816726000 KALAMATA 37.07 22.02 8 99S 39HIxxCO 4A 6WARM CROPS C 61816734000 METHONI 36.83 21.70 34 58R -9HIxxCO 1x-9WATER A 61816746000 SOUDA (AIRPOR 35.48 24.12 151 27R -9HIxxCO 3A-9WATER B 61816754000 HERAKLION (AI 35.33 25.18 39 88U 78HIxxCO 1A 3WARM CROPS C 62316310000 CAPO PALINURO 40.02 15.28 185 42R -9MVxxCO 1x-9WATER A 62316459000 CATANIA/SIGON 37.40 14.92 22 40U 403HIxxCO15A20MED. GRAZING B 62440250000 H-4 'IRWAISHE 32.50 38.20 688 691R -9FLDEno-9x-9HOT DESERT B 62440310000 MA'AN 30.17 35.78 1070 1042S 11HIxxno-9A 3WARM GRASS/SHRUBA 63822165000 KANIN NOS 68.65 43.30 49 5R -9FLxxCO 1x-9WATER A 63822602000 REBOLY 63.83 30.82 182 188R -9HIxxLA-9x-9MAIN TAIGA B 64214015000 LJUBLJANA/BEZ 46.07 14.52 298 319U 169MVxxno-9x-9WARM CROPS C 64308075000 BURGOS/VILLAF 42.37 -3.63 891 894U 118HIxxno-9A 3WARM FIELD WOODSC 64308215000 NAVACERRADA 40.78 -4.02 1888 1698R -9MVxxno-9x-9WARM CROPS B 64502196000 HAPARANDA 65.83 24.15 6 5R -9FLxxCO 3x-9COASTAL EDGES C 64740007000 ALEPPO 36.18 37.22 393 408U 639FLxxno-9A 2WARM CROPS C 64740022000 LATTAKIA 35.53 35.77 7 13U 126FLxxCO 1x-9WATER C 64740030000 HAMA 35.13 36.72 309 317U 137FLxxno-9A 2WARM IRRIGATED C 64740045000 DEIR EZZOR 35.32 40.15 212 221U 293FLxxno-9A 4WARM GRASS/SHRUBC 64917250000 NIGDE 37.97 34.68 1208 1364S 32MVxxno-9x-9MED. GRAZING C 64917255000 KAHRAMANMARAS 37.60 36.93 549 960U 136MVxxno-9x-9MED. GRAZING C 64917260000 GAZIANTEP 37.08 37.37 855 930U 300HIxxno-9x-9MED. GRAZING C 64917270000 URFA 37.13 38.77 547 630U 133FLxxno-9x-9MED. GRAZING C 64917280000 DIYARBAKIR 37.88 40.18 677 665U 170FLxxno-9A 1WARM GRASS/SHRUBB 64917282000 BATMAN 37.87 41.17 540 546U 64HIxxno-9x-9WARM GRASS/SHRUBB 64917285000 HAKKARI 37.57 43.77 1720 2446S 12MVxxno-9x-9WARM GRASS/SHRUBB 64917292000 MUGLA 37.20 28.35 646 790S 24MVxxCO25x-9MED. GRAZING B 64917300000 ANTALYA 36.70 30.73 57 40U 130HIxxCO 2x-9WATER A 64917340000 MERSIN 36.82 34.60 3 69U 152MVxxCO 1x-9MED. GRAZING C 64917370000 ISKENDERUN 36.58 36.17 3 213U 107MVxxCO 1x-9WARM MIXED C 64917375000 FINIKE 36.30 30.15 3 65R -9MVxxCO 1x-9WATER B 65206011000 THORSHAVN 62.02 -6.77 55 90S 12HIxxCO 1x-9TUNDRA B
Off the right hand edge of the table (not visible on some browsers) are some of the technical fields, like the A flag for “Airstation” (where you often see 1x-9 for a rural non-airport and 1A-9 for a “rural” airport. The A is airport while x is not.
You can shrink the font size or just look at the page source if you wish to see the rest of the record. The only ‘interesting bit’ other than the A flag is the imagination applied to the ‘terrain type’; where what used to be in a surrounding region when a map was made ages ago, is what is asserted to be present today (where Dallas Fort Worth Airport is described as warm fields and woods… in the midst of one of the more extended urban areas on the planet… ). If folks really care, I’ll put the same data in as ‘ragged right’ so you can see it easily.
Oh, and those first two numbers after the name are LAT and LON followed by reported elevation and elevation from a map grid. Then the Urban Suburban Rural flag. Also visible ought to be population in thousands and then the start of a block of codes (that includes the airstation flag). A -9 population is rural.
Ron Broberg (22:32:06) : Maybe you can post your station counting code …
grep ………..2010 v2.mean | cut -b 4-8 | sort -n -u | wc
Not that much different from yours. I’m prone to parameters in scripts, though, so I have work directories and years as passed parameters with defaults. That way the ‘process’ is consistent and I don’t have as much to worry about in the typo / qa process. Since the v2.mean file is already sorted by stationID, I don’t have a sort step:
WRK=${2-./data}
grep …………${1-2010} $WRK/v2.mean | cut -b 1-11 | uniq > $WRK/$1_uniq_station_list
and then I do things like “wc -l” on the ouput list or diff or…
I suspect that the difference in results is due to provenance of the data. It does have a ‘today’ update date on the ftp server and my copy is from 4 days ago.
And, given their rather ersatz ‘process’ as described by the folks who ought to know this the most (the leader of the unit in the UK) it looks like updates can happen at any time…
Oh yes – all Czech thermometers were scraped. Why couldn’t they leave at least Milesovka – it’s nice professional station at the mountain top with a record from the end of 20’s.
http://travel.webshots.com/photo/1038138769028455201hytgZu
Wait a month or two, then get back to us.
I make that – Stations Dropped:
Africa – 118
Asia – 137
S America – 62
N&C America – 59
Pacific Reg – 39
Europe – 70
Antarctica – 1
For Europe – using database-derived trends for GISS adjusted data:
65 of the 70 dropped stations were in the database – the 5 missing ones may be below the QC threshold
Average trend for ALL European Stations: 0.56 Deg C/Century warming
Average trend for Dropped European Stations: 1.23 Deg C/Century warming
Average trend for Remaining European Stations: 0.5 Deg C/Century warming
So for Europe at least, dropping these thermometers MAY not have a warming effect. However, these trends are for all years – it depends on the forward trends at the remaining stations.
@mILLrAT (13:04:40) :
“I have converted the station list into a google earth kml file that is available for download at
http://cid-78d84fe53bde5e59.skydrive.live.com/self.aspx/Public/RIPtempStations.kml”
Thank you Sir!
(the file ext. is found as *.xml – just rename to *.kml)
…3 stations left in Denmark, 1 in Copenhagen (lagest city), 1 in Aalborg (4 th. lagest city), and the last (Roenne, Bornholm) on a smal iland in the middle of a parking lot
..an on a funny note: they left out the one in Tarm, a Danish syn. for “anus”…
again, your work is highly appreciated!
“E.M.Smith (19:29:57) :
Andrew30 (16:57:24) : Is this a temperature scale conversion, F to C, if so should the 50.0 not actually be 5.0?
The data are in 1/10 C increments, so 102 is 10.2 F.”
You’ve got a typo, you mean “102 is 10.2 C”. Andrew, sometimes programmers multiply a float with a value that is usually a power of 10 or power of 2 like 256 and store the product in an integer. From there they use fixed-point arithmetic. Often done in economy where you want exact dollar/cents (you multiply by 100 in this case) and avoid the inability of floating point numbers to exactly represent certain fractions – sometimes you get a pocket calculator throwing something like 0.999999999 at you when you know it should say 1 – this is such an artefact.
This is legit, only the multiplication/division they did was buggy.
Offhand it looks like I surmised correctly. The goal is to establish there is a long-term strong warming trend. They have adjusted individual station data downward in the far past but upward in the near past. However this was done clumsily and has been detected at Darwin etc. Their ignoring of UHI and the proper adjustments has also been noted.
Realizing they will be facing increased scrutiny, they are placing their bets on stations that will show an increased warming trend. The high altitude stations will not show that, so they are eliminated. Urban thermometers that have bottomed-out on UHI and will now report anomalies more consistent with real global temperatures, were removed. For example, note the dropping of the Dallas-Fort Worth airport. It seems unlikely there will be a large increase in air travel anytime soon, and between current economic conditions and theoretical upcoming “green taxes” air travel may likely decrease, thus it will not show a great warming trend, thus it is dropped.
What is left appear to be stations where nearby development with UHI will bias the readings to a warm trend in the coming years. They went light on the suburban deletions, as increased populations and future economic development will make suburbs warmer. There are rural stations that are unlikely to see nearby development anytime soon, may even be showing cooling, thus they are good candidates for deletion. But rural stations that will see development and thus increases would be kept, including those that now or in the future should not be labeled “rural.”
Of course far more research needs to be done as to the specific deletions and retentions to positively conclude the result will likely yield an increased artificial warming trend, in line with AGW predictions. But offhand, to me, I can believe that until shown otherwise.
… it looks like updates can happen at any time…
Which is unsurprising to me when dealing with international data sets
I also occasionally take a look at the EIA world oil production numbers. While interim updates are published more-or-less on a monthly schedule, the data effected can go back two years. Estimates are used for oil production in countries that don’t report in a timely fashion, and those estimates are updated whenever a particular country gets around to providing more accurate figures.
Those estimates can affect things like total world oil production. Early figures in 2009, for instance, suggested that annual oil production reached a maximum in 2008. Current figures suggest 2005. (See 4.1d). (And the ‘max’ statement is a statement of past history, not a future prediction)
http://www.eia.doe.gov/ipm/supply.html
So I’m used to seeing international data sets – even on “very important topics” – shift a bit. Not everyone reports in a timely fashion. The major difference here seems to be that NOAA has enough thermometers in play that it does not need to make estimates for stations that haven’t reported yet.
My prediction: more stations in the data set for 2010 next time it is updated.
“DirkH (08:35:35) :
[…]
This is legit, only the multiplication/division they did was buggy.”
Oh well, and they should have thought of the fact that nint truncates, not rounds, so they should have added 0.5 before the truncation so as to not introduce bias.
“DirkH (08:43:01) :
[..]
Oh well, and they should have thought of the fact that nint truncates, not rounds, so they should have added 0.5 before the truncation so as to not introduce bias.”
Dang! correcting myself. It rounds. Sorry not being a Fortran specialist and talking out of my ass again. So that’s a wrong assertion of mine, thank you, google.
Co isn’t analogous to CO2, because CO2 is much more inert. CO is taken up by red blood corpuscles in a way that is effectively poisonous. It’s qualitatively bad, unlike CO2.
E.M., i just saw on your blog that the people who try to rewrite GISTEMP in Python continue the tradition of omitting brackets where they can. That means they will get different undefined artefacts than the Fortran original but undefined artefacts it will be. Good luck Python guys. Go to E.M.’s blog to the thread he linked to to see my comment.
Well, I’ve just completed a new download of the v2.mean.Z file followed by unpacking and a “diff” with the 8 Feb 2010 version.
The most interesting difference is this one:
< 4347898800032009 264 260 261 274 278 281-9999 289 295 290 288-9999
> 4347898800032009 264 260 261 274 278 281-9999 289 295 290 288 278
> 4347898800032010 274-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999-9999
Notice that, in addition to putting IN the 2010 record for this station, the 2009 record has had a December value added.
So between 8 Feb 2010 and now, Dec 2009 was “discovered” somewhere and put in. So even a month and a half after the fact, lost thermometers can be found.
There were 67 other “adds” to the file
So at this point, it looks like when NOAA make a file available, it’s only a suggestion not an endorsement, and it will be constantly changed, day by day, for months. Given that each month there will be a new month of data: any single day the image of the file may well be different from any other day but with a ’spike’ of newness near the 2nd week of the month.
How does one assure any consistency of processing or comparison of results between researchers when the base data is constantly mutated? How does one “measure” the process or even standardize the error detection? Unless you know the DAY that GISS chooses to do their copy of the GHCN input, you can not duplicate their results (though you could come “close” most of the time.) But given the tendency to ’spread’ a value 1200 km in GIStemp, that single December added value could influence a box of space 2400 km x 2400 km and that could also shift hemispheric values, etc.
Just amazing.
Here’s the monthly history for DFW AP
JAN 2010
http://www.wunderground.com/history/airport/KDFW/2010/1/13/MonthlyHistory.html
DEC 2009
http://www.wunderground.com/history/airport/KDFW/2009/12/31/MonthlyHistory.html
JAN mean is 45F
DEC mean is 43F
Here’s Chiefio’s GHCN station reference: (*) Dallas-Fort W 32.9 N 97.0 W 425722590000 4,037,000 1947 – 2009
Checking NCDC’s MMS database it shows it to be current, but curiously, shows a start date of 1974 NOT 1947 so I wonder if the start date is a typo? According to AP history records, DFW Airport opened for commercial service on January 13, 1974. Sure looks like a typo in the GHCN database to me.
I thought maybe the issue has to do with METAR reporting, as I have
previously pointed out to have data transmission errors. So I went through every hourly METAR for Dec09
Starting here and working backwards through Dec09 and forwards through Jan10:
http://www.wunderground.com/history/airport/KDFW/2009/12/31/DailyHistory.html
(be sure to click “show full METARS”)
Every METAR report for every hour of the month of December checks out. As does every one on January 2010
So if they are using DFW AP data, and the Lat/Lon given ( 32.9 N 97.0 W) places it there, see…
http://maps.google.com/maps?q=32.9+N+97.0+W&oe=utf-8&client=firefox-a&ie=UTF8&hq=&hnear=%2B32%C2%B0+54%27+0.00%22,+-97%C2%B0+0%27+0.00%22&gl=us&ei=6dJ2S_v5BIPMsgPH073LCA&ved=0CAgQ8gEwAA&ll=32.9,-97&spn=0.119052,0.128574&z=13
…then there’s nothing wrong with the raw data that I can find.
So it puts the onus on NCDC’s algorithms.
I don’t see why this is so surprising to you. The most recent month(s) continue getting updated over time, as the data come in. I find it strange that your first thought was that it’s all due to a “hatred” of thermometers.
You must have other, older versions of v2.mean lying around. Just do the same comparisons on them.
“you can not duplicate their results (though you could come “close” most of the time”
Has GISS even updated their webpage for Jan 2010 results yet? Not that I can see. I do think they wait until they think enough stations are in. But yes, the numbers change do change a hair as more updates come in. You can see this for yourself, and I think it’s been noted on this website.
“It also shows that the excuse of things being dropped for not electronically reporting is pretty much a lie, too. I note that Dallas Fort Worth Airport..”
Care to re-word that?
@ur momisugly E.M. Smith
It also shows that the excuse of things being dropped for not electronically reporting is pretty much a lie, too. I note that Dallas Fort Worth Airport is on this list and I’m pretty sure they have electronic reporting…
For the 2010 deletions, “That dog won’t hunt”… since BY DEFINITION those stations were reporting up until now.
I notice your “update” statement that DFW is indeed a failed QC station.
Are you going to retract your “pretty much a lie” statement?
Ok, enough of my complaint …
Nah. Say it aint so … 😉
Or maybe it isn’t sarcastic… maybe in our Orwellian world… No, no, must not think that way. Where did I leave my soma?…
So, no, I don’t see much reason to ‘keep power dry’. I could easily see a single digit number of thermometers change from “QA failed” being itself QA’d but if they start putting 5% or more of the records ‘back in’ I think they are violating their published methodology… (though I’d welcome it).
Really? You would “welcome it?”
So at this point, it looks like when NOAA make a file available, it’s only a suggestion not an endorsement, and it will be constantly changed, day by day, for months. …
… Just amazing.
I’ll assume your ‘amazement’ comes with an undertone of ‘welcoming’ 😉
—————
kadaka wrote:The goal is to establish there is a long-term strong warming trend.
See vjones’ work below.
vjones wrote:Average trend for ALL European Stations: 0.56 Deg C/Century warming
Average trend for Dropped European Stations: 1.23 Deg C/Century warming
Average trend for Remaining European Stations: 0.5 Deg C/Century warming
Thanks for that update. I appreciate it.
A small shadow cast on the thesis that: NOAA is selectively removing cooling stations.
In this case, the stations dropped for Europe were warming stations.
“…then there’s nothing wrong with the raw data that I can find.
So it puts the onus on NCDC’s algorithms.”
Or, somebody/something messed up when coding in the CLIMAT report. You can look it up, and it shows the weird numbers that caused it to fail QC.
What I find amazing is that any scientist would not be horrified by this process. All data should be held out and made official on a specific date. With billions going for climate research, a new website to promote AGW and a new computer in WY, you’d think someone might consider updating the methodology to at least the 16th century.
I guess not.
Some airports going away, eh? Isn’t it pretty much SOP for this bunch when criticised with logic and facts, to 1). Tell the public it is unfair criticism by a bunch of skunks-at-the-garden-party that obviously has no substantive impact. . . and then 2). Run around behind the scenes going “Hmm, that does have some merit after all” and address it without comment or admission of why?
Ron Broberg (11:44:27) :
(…)
A small shadow cast on the thesis that: NOAA is selectively removing cooling stations.
In this case, the stations dropped for Europe were warming stations.
And amazingly enough, that wasn’t even my thesis. Or my hypothesis.
As you presented, the European stations that have shown great warming have been dropped. As I surmised. They have already been milked for the greatest positive change in rate of warming. UHI and other factors have taken place, they will now show a rate consistent with the rate for global average temperatures. The ones retained, I surmised, have the greatest potential to show the greatest positive change in rate of warming in the future.
The first set has been milked dry, now they are moving on to the next set. By creative selection of stations, they will have their great rate of warming without resorting to messy and detectable mis-adjustments of the raw data.
Try again.
@Anthony: The GISS web site shows a “GHCN + USHCN” record that starts in 1947:
http://data.giss.nasa.gov/cgi-bin/gistemp/gistemp_station.py?id=425722590000&data_set=0&num_neighbors=1
A look in the v2.mean file shows it is in GHCN:
Though that 1947 record is just a December value.
So I’m left to assume there was something recording there long ago. Perhaps some older rural airport prior to DFW being created? If so, that begs the question of how one mod flag spans so much time and change. If not, that begs the question of where the data came from. In either case, it’s an interesting question of station and data quality and provenance.
If there are any Dallas locals who know the history, perhaps they could speak up.
Oh, and in 2009 it had a couple of data dropouts in Sept and Oct as well.
Or has them now? Or might have them in the future, but maybe not?
In the mean time, having established that GHCN v2.mean is a perpetual “work in progress”: that complicates picking a new ‘poster child’ for electronic reporting and “dropped”. It will be easy to identify an electronic reporting and “missing in action”, but then there is that problem of prodigal thermometers returning months later.
The other interesting path this leads to is the question of just how much GIStemp products have “stability”. If the data can be MIA for a few months, then show up, how much “faith” can be put in any claims of “Warmest” or “Most Extreme” anything? WHEN does a GIStemp product become ‘stable’?
Best I can think of is to get a copy of GHCN at the moment any GISS claim is made and do a “missing data” analysis on it. What fraction of stations in the current month have “missing data” compared to ??? ( 6 months before? A year before? ) but even that becomes a bit of a random act. If the claim is made the 22 of the month, was the data downloaded by GISS on the 20th? The 15th? Did NOAA provide updates on the 21st?
For example:
http://data.giss.nasa.gov/cgi-bin/gistemp/gistemp_station.py?id=434789880003&data_set=0&num_neighbors=1
that station with the December Return. It has a 2009 “average” on the GISS graph. It does not include December. In a few (days? weeks?) it will. How would you know that the value in a few weeks is based on different data from the value now without a detailed data mining that just about nobody on the planet will do? Does it matter?
How often do the GISS published charts change? And by how much? Is it significant?
I don’t see an easy way to answer those QA questions. ( And “trust me” or “guess it’s OK” are not valid QA processes.)
(In accounting, there are similar issues. So you have a moment in time where you issue your annual report. You may ‘restate your numbers’ after an audit in some future year or in next year’s annual report, but that becomes part of the record. it stands out if every year you have “restated last years earnings lower 10%” for a few years. Here in GHCN / GISS that ‘restatement’ is an ongoing and un-audited process in perpetuity… )
But at least now we start to have a handle on why so many people have saved images of various GISS graphs or done data plots only to find they don’t quite match later. It’s all about the stability and provenance of the base data, and those are ill defined.
Then blend that with the GIStemp homogenizing that re-imagines the past based on changes in the present and you have a foundation of the past made of sand.
Really, what’s the points of these posts on mass dying of thermometers, when all “being eaten” means is that the stations weren’t among the first batch to report for the month? So folks speculate on why Greenland is being dropped, on the basis that there weren’t many stations in the list reporting Jan results by 8 Feb. Then we look on 13 Feb and amazing, there are six more! Good, so we can have the same discussion next month.
what’s the points of these posts on mass dying of thermometers
I’m assuming this is rhetorical, but just in case anyone needs it spelled out …
The point is to create an atmosphere of doubt and uncertainty. Two prongs of the stratagem known as: FUD
Fear is fed by the stories of ‘one world government carbon taxing us into the stone age.’
One response to FUD is to examine the details. In this case, DFW was raised as a rhetorical point by EM Smith to cast doubt on NOAA’s claims that stations are dropped if they aren’t reporting electronically.
I subsequently ‘found’ DFW in the v2.mean.failed.qc file. All I had to do was look. It was never lost. It was processed by NOAA and found wanting. E.M Smith was apparently too unfamiliar with the NOAA GHCN data set to be aware of the file.
Why NOAA v2.mean had a processed monthly mean of -6C is an interesting question. It is unlikely to be resolved in this thread. But NOAA GHCN was correct to reject their monthly mean for DFW (which was -6C). As I noted and Anthony followed on, METAR data is available for DFW in Jan 2010. It provides a monthly mean of +6C. I don’t think that tells us much about why NOAA did not receive their CLIMAT data updates or were not able to process them. DFW has values for onlu the first 10 days of January in the GHCN daily file for that station.
Of course, DFW was just an exemplar. Long lists of other stations were held out as more evidence of deliberate manipulation by an agency which was accused of ‘pretty much lying.’ E.M. Smith suggested he would ‘welcome’ seeing that list made shorter, missing stations added. When it became obvious that is in fact what happened in the 4-5 days between Feb 8 and Feb 12, he responded with pointed questions which suggest his ‘welcome’ was less than warm and friendly. From here, it appears that it is more important for him to hold on to the “theme” – to bolster the stratagem – to spread as much ‘uncertainty and doubt’ as possible – then to welcome the additional data sets. Hopefully, E.M. Smith’s welcome will be warmer as the additional stations accumulate next month and throughout the rest of the year.
As I said, all this seems fairly obvious. I’m just spelling it out on the off-chance the question was not rhetorical.
E.M.Smith (14:44:19) :
“If the data can be MIA for a few months, then show up, how much “faith” can be put in any claims of “Warmest” or “Most Extreme” anything?”
I’ve seen GISS monthly global anomalies get revised by upto +/- 0.02 C. You should realise there are uncertainty bounds on these numbers. If 2 years or months are within those bounds of each other, you can’t say one is warmer than the other. For example, a lot of breath is wasted here about whether 1934 or 1998 was warmer in the US, when they’re really just statistically tied. On the other hand, the difference between the 2000s, 1990s, 1980s and 1970s averages are significant.
But again, you’ll notice that GISS hasn’t put out Jan 2010 numbers yet. But you’ve got the GISS code running. Why don’t you just run it for the two different v2.means, and see what happens? Maybe you’ll see the reason why GISS is holding back on Jan 2010; I don’t know.
But in any case, I’m still wondering if you care to reword certain rash statements made above.
Ron Broberg (17:07:40) :
Thank you to you for actually looking into things. As for DFW, you can look up the CLIMAT report and see it for yourself. It has the numbers GHCN logged. I can’t speculate what went wrong where, but maybe we can watch it to see if it gets corrected.
The Giss monthly update normally occurs the middle of each month.