NOAA langoliers eat another 1/3 of stations from GHCN database

Dallas Fort Worth airport is one of hundreds of GHCN reporting stations gone missing. GHCN stations are becoming an endangered species.

Updated frame from the movie "The Langoliers" 1995, - with apologies to Steven King's book

 

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.

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Wasn’t there already a dearth of stations in Africa already?

b.poli

The only station that will remain is the one above Karl’s and Hansen’s Bunsen burner in their labs.
OT – I know. 🙂

What am I missing? I thought we want to drop airports because they show artificial heating…

Andy

How does this list stack up next to the lists of stations that meet or do not meet the technical standards noted in the surface stations report?
In other words, are these good stations or bad stations? or is there any other correlation?

layne Blanchard

I didn’t realize North America was dominated by such tropical locals. 🙂
Oh well. It’s snowing in FL also right now.

OT Gordon Brown is at it again – numpty
http://www.guardian.co.uk/environment/2010/feb/12/gordon-brown-climate-change-fundraising
“But Mr Brown brushed aside the sceptics’ challenge during a UN webcast to launch the group today.
“Those people who have become global warming deniers and those people who have become climate change deniers are against the grain of all the evidence that has been assembled that global warming and climate change are indeed challenges that the world must meet and that can only be met together,” he said. He has previously denounced what he described as “anti-science, flat-earth climate sceptics”.”

Henry chance

Some are located where there is just too much cold and snow and the checkers have to travel in the mud away from all weather black asphalt surfaces. Pruning makes the data stronger (More robust)

DanD

Did anyone else notice “Batman?!”

Mike Ramsey

Question number five answered by Dr. Gavin Schmidt, a climate researcher at NASA’s Goddard Institute for Space Studies (GISS) in New York City.
“5. What about the meteorological stations? There have been suggestions that some of the stations are located in the wrong place, are using outdated instrumentation, etc.
Global weather services gather far more data than we need. To get the structure of the monthly or yearly temperature changes over the United States, for example, you’d need just a handful of stations, but there are actually some 1,100 of them. You could throw out 50 percent of the station data or more, and you’d get basically the same answers. Individual stations do get old and break down, since they’re exposed to the elements, but this is just one of things that NOAA [the National Oceanic and Atmospheric Administration] has to deal with. One recent innovation is the set up of a climate reference network alongside the current stations so that they can look for potentially serious issues on the large scale — and they haven’t found any yet.”
http://climate.nasa.gov/news/index.cfm?FuseAction=ShowNews&NewsID=248
“… haven’t found any yet.” Hmmm, Thank you God, for making our foes so easy to take down.
Mike Ramsey

Peter Dare

In the Africa list, I note that stations 80-99 are all in the Republic of Sudan spanning the northern tropical zone from about 8-22N latitude. The sites cover the capital city and all the major regional towns throughout this vast country, from the desert north through the Sahel and savannah zones south to the edge of the rain forest. In effect, Sudan has been deleted from the climate recording map. It is possible/likely that the meteorological recording system has broken down completely, given the frequent internal political instability/conflicts across much of Sudan over ecent decades.
Many other deleted stations refer to north-west African countries.

Robert M

I would be interested in seeing if there is any sort of pattern to the station dropouts… Is it possible to tell if a person is selecting whether or not to include a station.
I know that everytime these guy get caught, they cliam that the changes are not sinister in nature, but simply a mistake. But if the dropouts are nefarious in nature, it is possible that simply looking at the individual station droput data might not show any trends, but I bet they allow other nearby stations that show more recent warming (or earlier cooler temps) to extend their effect.
One thing is sure, there is an agenda here, it just needs to be teased out.

Well, it will be a lot easier to to the “adjustments” to fewer stations now !!!

Somebody should take EM’s work and do a google map before and after.

tty

Interesting to see that they dropped Haparanda. You can get the hourly readings in real time here:
http://www.smhi.se/vadret/vadret-i-sverige/observationer#
Haparanda is also one of the sites with longest continuous record at high latitudes anywhere in the World (it has records back to 1802), and is, while not exactly rural, a rather small town.

Robert M

Seems I can’t type today, cliam should have been claim…

mpaul

You are confusing cause and effect. The thermometers are going extinct *because* of Global Warming. It will be in AR5. In fact, at this rate all temperature stations will likly be extinct by 2035 according to WWF.

Maybe they realize that satellite data is superior, so they are slowly winding down the surface thermometer mess.

Joe

It will be pretty hard to pull all the reading centers as we still have uncontrolled…ops CBC, ummm, controlled televison stations.
Ah well we still have the uncencored…oh no the climate cops….
censored internet.

DirkH

They killed my hometown, Braunschweig, Germany. They must have found out i’m a skeptic. Or maybe it didn’t warm enough: The station is at a small airport that is not tarmacked, and it’s outside the city near a forest, so not much UHI.
It can be found easily by searching for this in google maps:
Flughafen Braunschweig-Wolfsburg

Crikey – they’ve taken out most of France!
Don’t they like the Fwench?
There doesn’t seem to be reason behind this, like taking out all ‘U’, or all ‘R’ stations: the thermometers are dying across the board.

Mike Ramsey

DanD (10:22:28) :
Did anyone else notice “Batman?!”
I think that Batman is a city in Turkey.
Mike Ramsey

I don’t see 1 station in the UK or Ireland! Am I missing something?

Chris H

I guess this comes as no surprise as it transgresses every rule of data collection. In my simplicity, I would reckon that for a global temperature average one would take as many stations as one could get and correct for the number of stations per unit area so that well covered areas did not skew the mean. Adjustment for UHI would be reasonable but that’s it. Dealing with missing values is standard statistical practice and would not trouble a decent statistician.
Even if it is reasonable to drop some stations for incomplete data, the values from those stations should be reported to check that they are representative of the retained stations. Epidemiology 101.
This is what we jokingly used to call data enrichment. I never thought I would see it for real from supposedly “top” research establishments

just because NOAA and GCHN have stopped using their data doesn’t mean they have stopped gathering and reporting. We need the “real” raw data, not just the filtered raw data. That would allow us to correlate the dropped staion data against the remaining to see if there is a discrenable bias. By keep the raw data out of the worlds hands they are setting the playing field in their favor.

Ken Harvey

I notice that Durban Airport has been given the chop. I cannot imagine why. Its surrounds are described as “water”. Well, yes, it has the Indian Ocean along one side, but on the other it has the outskirts of a city with a reputed population of 5M. (probably only 3M or 4M or so in fact).

JonesII

I guess surfacestations.org will have to hire a detective team. This is no longer about metereology, so its becoming less interesting.
The trouble is what kind of experts will be needed in the future for finding all missing data; archeologists, cryptologists or criminologits?☺. Well, real data is lost for ever anyway.

DirkH

I havde to add there is no political unrest in my hometown ATM, unlike Sudan, and, glancing at google i see the Braunschweig airport does have one tarmacked runway now – probably the people at Volkswagen paid for one, their managers use this airport with a Learjet or something like that.

Sean Peake

No Canada… why mostly sweaty places?

Gary Hladik

Mike Ramsey (10:24:13), that reminds me of Isaac Asimov’s 1955 short story “Franchise”. In that story the supercomputer “Multivac” decides all US elections by interviewing a single voter who’s so average that he represents the entire electorate.
Hey, the “average surface temperature of the Earth” is a number so nebulous and utterly useless that NASA might just as well derive it from a single thermometer and save us all a few bucks.

Sean Peake

Thinking more about this. I guess, now that the science is settled and the end is (Bill) Nye unless we do something, there is no need to rely on temperature stations.

TerrySkinner

I saw a map a few days ago (maybe here, maybe not) where all the poorly or non-measured areas showed up as warmer including the Arctic, Siberia and N. Africa.
Of course in the past few months Europe, China, USA etc must have had a lot of cold readings. Chances are they are for the ax next.
However roll forward a few years. What’s the chance the die hard AGW supporters will use 2009/2010 as a new baseline of cold to show ‘unprecedented’ warming over the next few years?

Henry chance

Schmidt and his legacy thermometers. The old ones are tired and need a little help. We have snowfall in all 57 states. Is that showing up on a map?

Roger Knights

Many other deleted stations refer to north-west African countries.

Don’t you mean northeast?

kadaka

Plato Says (10:19:31) :
OT Gordon Brown is at it again – numpty
(…)

Curious. “Global warming deniers” and “climate change deniers” are now identified as being separate groups. Perhaps there are enough of them now to differentiate based on the slight but noticeable differences, thus leading to declaring them separate species. Evolution in action, as populations grow to fill enticing and expanding niches.
Didn’t Michael Mann, with his hockey stick, deny there was either climate change or global warming before Modern Industrialization? Thus it is allowable to be “anti-science, flat-earth climate sceptics” with regards to historical times, but not more modern ones?

Sean

The actual number of records is just way to low. If the professionals are unable to collect the temp, or think it can be restricted by dislosure agreements, there are other sources. Many amateurs like to collect temp readings, and business do for commercial reasons also. It should be practical to do an open call to the public to provide long station records. I suspect there are schools, sea ports, ice cream makers, farms, ski resorts which have 20 years records. Even if you set the limit at 50 years, I think we would find significant numbers Of course, you still need QA, but this is easier if there is a direct dialogue with the supplier.

Honest ABE

Mike Ramsey (10:50:03) :
“I think that Batman is a city in Turkey.”
Ridiculous, bats are mammals not birds.

James Sexton

Did I miss it? What does the A, B, or C represent at the end of the row? And why is Mexico such a target? Are the thermometers getting kidnapped too??!!!

It's always Marcia, Marcia

Dallas Fort Worth airport is one of hundreds of GHCN reporting stations gone missing.
Because it’s too cold in Dallas now?

James Sexton

Yikes!!! First Bolivia and now they’re going after Paraguay!!!

Mark Young (10:07:42) :
Wasn’t there already a dearth of stations in Africa already?

Yup. The large holey areas just got more holey…
Leif Svalgaard (10:13:22) : What am I missing? I thought we want to drop airports because they show artificial heating…
I don’t want to drop any stations. I want the data to clearly state what is happening and for change to be reportable by group (such as Airports vs rural vs Urban vs …) so see what’s contributing to the means.
With that said: Dropping an airport can still induce an upward bias. Say, for example DFW was in the ‘baseline to now’ period (and so it STAYS in the baseline). And say it was cooler in the baseline (pre -Jets) and ‘warmed the planet’ until now. But since, oh, 1990 or so it has not changed to be much warmer (i.e. traffic is down and they are not adding more tarmac). It’s just not adding any new ‘lift’. So you drop it. But if you leave in a nearby place that is still growing, it will now be showing increases of “anomaly” when compared to the prior values of DFW and those increased values will be used to “fill in” DFW that will then be compared to it’s prior self… and found to be warming.
And yes, GIStemp compares “old basket of thermometers” to “new basket of thermometers” when computing “grid box anomalies”. It does not compute anomalies as ‘thermometer to self”… except by accident if that’s all it’s got in a box.
So change itself is a problem.

Clive

Someone may have asked.
I dunno…it just seems that vast areas are under represented a la the Bolivia Syndrome.
Are these stations pinpointed on a world map somewhere?
Just curious.
Thanks,
Clive

According to Gavin Schmidt, you only need a handful of thermometers to accurately represent the mean temperature of the planet earth. Conveniently, these handful of thermometers are all located in urban environments, and what they read doesn’t matter anyway, because Schmidt will just aimlessly wander over to Hansen’s office and they will adjust the earlier times down and the more recent times up.
Gotta keep that global warming afloat!

It's always Marcia, Marcia

extinction or culling?

It's always Marcia, Marcia

E.M.Smith (11:45:29) :
There you go again E.M., explaining things so it’s easy to understand.
🙂

KevinM

In plots, the UHI seems to be more of a step than a ramp. In the Russian stations, for instance, It appeared to be a slight ramp for 10 years, then a steep increase for ten years, then a levelling off afterward.
If you trim data from UHI sites like airports _after_ the UHI step (using the UHI excuse), then you maximize the effect of UHI on the aggregate series rather than minimize it.
On the other hand, if you trim data from UHI sites like airports by removing the site and its entire history, you will get the most accurate picture for a number of sites that might be to small to be counted as a global proxy.
On the other hand, if you accept UHI error by not correcting (by deletion) for it at all, then the average sum of the staggered anomoly steps will form a ramp that starts around the 1950s, then correlates well with fossil fuel use (a proxy for urbanization), then stabilizes when the bulk of your sites has passed the “step”. You would then approach an accurate anomoly measurement again (with readings offset from pre-UHI by a static error).
I think (conspiracy theory) the thermometer team has been gaming these three scenarios, and has maybe painted itself into a corner by exhausting sources of UHI step.

jeanparisot

Global weather services gather far more data than we need. To get the structure of the monthly or yearly temperature changes over the United States, for example, you’d need just a handful of stations, but there are actually some 1,100 of them. You could throw out 50 percent of the station data or more, and you’d get basically the same answers. — Gavin
If the distribution is even and random, you might get the same answers. If you carefully select which half to throw out one could introduce confirmation bias. Since the advent of modern data processing, when has too much data ever been a problem.

NickB.

Mike Ramsey (10:24:13) :….Anthony
Has anyone taken a look at the reference network products, or their siting yet? I’d be curious if these actually fit with the GISS products or not, assuming they’re not adjusted or otherwise shenaniganized…
http://www.ncdc.noaa.gov/crn/

anna v

There are 10 stations from Greece. I wonder if any are left because the ones taken out seem to cover the country!
We have had a cool summer and a medium winter. Maybe it is the cool summer that axed them?

kadaka

So are they now set up to declare Africa has become a hotter and more arid desolate wasteland in the years to come, exactly as forecast? Have they properly pared down the weather stations elsewhere so their predictions will be proven true?

James Sexton (11:39:32) : Did I miss it? What does the A, B, or C represent at the end of the row? And why is Mexico such a target? Are the thermometers getting kidnapped too??!!!
For Mexico, a traunch was added some years back in The Megathermal Zone. A casual look at the Mexican deletions look like more up toward the Sierra Madre mountains. They don’t like Mountains at NOAA… Japan has no thermometer above 300 M any more, so, I suspect, will the rest of the world once they are done…
I found where they kept the data and descriptions once, and kept track of it here:
http://chiefio.wordpress.com/2009/02/24/ghcn-global-historical-climate-network/
For those wondering what all the misc flag characters mean, the “documentation” provided as described on that link (BEGIN QUOTE):
A detailed description of GHCN’s Quality Control can be
found through http://www.ncdc.noaa.gov/ghcn/ghcn.html.
So, there you go. Some pretty good pointers to where to get bits and what they mean. But what about these “read.inv.f” and “read.data.f” programs it mentions? Well, I didn’t see them. But I did see one named “v2.read.data.f” that seems to do the same thing.
The comment block from down in the guts of that program does a nice job of telling you what the fields are:
c ic=3 digit country code; the first digit represents WMO region/continent
c iwmo=5 digit WMO station number
c imod=3 digit modifier; 000 means the station is probably the WMO
c station; 001, etc. mean the station is near that WMO station
c name=30 character station name
c rlat=latitude in degrees.hundredths of degrees, negative = South of Eq.
c rlong=longitude in degrees.hundredths of degrees, – = West
c ielevs=station elevation in meters, missing is -999
c ielevg=station elevation interpolated from TerrainBase gridded data set
c pop=1 character population assessment: R = rural (not associated
c with a town of >10,000 population), S = associated with a small
c town (10,000-50,000), U = associated with an urban area (>50,000)
c ipop=population of the small town or urban area (needs to be multiplied
c by 1,000). If rural, no analysis: -9.
c topo=general topography around the station: FL flat; HI hilly,
c MT mountain top; MV mountainous valley or at least not on the top
c of a mountain.
c stveg=general vegetation near the station based on Operational
c Navigation Charts; MA marsh; FO forested; IC ice; DE desert;
c CL clear or open;
c not all stations have this information in which case: xx.
c stloc=station location based on 3 specific criteria:
c Is the station on an island smaller than 100 km**2 or
c narrower than 10 km in width at the point of the
c station? IS;
c Is the station is within 30 km from the coast? CO;
c Is the station is next to a large (> 25 km**2) lake? LA;
c A station may be all three but only labeled with one with
c the priority IS, CO, then LA. If none of the above: no.
c iloc=if the station is CO, iloc is the distance in km to the coast.
c If station is not coastal: -9.
c airstn=A if the station is at an airport; otherwise x
c itowndis=the distance in km from the airport to its associated
c small town or urban center (not relevant for rural airports
c or non airport stations in which case: -9)
c grveg=gridded vegetation for the 0.5×0.5 degree grid point closest
c to the station from a gridded vegetation data base. 16 characters.
c A more complete description of these metadata are available in
c other documentation
Unfortunately, it does not tell you just what that ‘other documentation’ might be nor where to find it…
So you will notice that the far right A,B,C is um, er, “not clearly defined” but you can go look in “other documentation”… somewhere…