
South American Aridity Map
Original very large image. This map has no copyright notice on it, and was funded by U.N. grants and government entities. It is my belief that given the educational non-commercial nature of this use, and the funding and lack of copyright on the map, that this use constitutes “fair use”.
Earlier, we looked at both Brazil and Argentina in isolation. Argentina had a fairly stable thermometer history, and a fairly stable temperature history. Brazil had some northward migration of thermometers, though with a certain Samaba rhythm of ebb and flow in the movement north. Here we will be doing what we did for the Pacific Basin. Looking at the entire South American set, with the large and somewhat variable part, Brazil, taken out. Answering the question: How stable is Latin America if the one large known source of variation is set aside?
The answer is: Very Stable. Almost enough to put you to sleep; once things stabilize about 1951. It is, in summary, a South American Siesta. If there is “Global Warming”, it is asleep at the switch in Latin America.
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South America, the Temperature History in GHCN
You get a rather more interesting story looking at South America as a whole. I’ve done something a little unusual here in that I’m using asymmetrical and non-linear banding. It just shows what is happening better, but be aware of the normal human bias to expect both linearity and symmetry… We still have South Pole on the far left and “toward the North Pole” on the far right. The south pole band covers up to latitude 50 S. That’s that “Cold Near Polar Tip” band. We then step by a 10 degree increment up to 40 S, about the top of the “Cool Patagonia” band. From that point, it is 5 degree bands to the “near the equator” at 10 S. Roughly the end of the cooler higher altitude band of Brazil. We then have a very fat 20 degree band that reaches to 10 degrees each side of the equator. The equator is a more stable place and this band captures that equatorial heat in one place. Finally we have the “10 N to the Pole” band that separates out that Caribbean Coastal area.
Among the more interesting bits is how the first thermometer starts out at the Equatorial band, then jumps wholesale to the Argentine Pampas band. The spreading begins from there, with a gross overrepresentation of that near polar tip band from 1909 to 1939 decade ending (which explains a lot of the cold bias we see in the early years a bit lower down.) And while, by 1949 decade ending, we start to have stability, there is still an upward drift in the equatorial coverage and coastal Caribbean tropical zones at the expense of the 30 S and 35 S zones. The net effect being a modest migration from the Pampas temperate zone to the equatorial and Caribbean tropical. We would expect to see significant warming over the life of the temperature series from these changes, but moderating in later years with 1969 onward being most stable.
This is the usual South Pole on the left, North Pole on the right.
What does South America look like? The decade changes by latitude look like this:
Look at ./Lats/Therm.by.lat3.Dec.LAT (Y/N)? y Year SP -50 -40 -35 -30 -25 -20 -15 -10 10 -NP DecPct: 1849 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 100.0 DecPct: 1859 0.0 0.0 0.0 28.6 0.0 0.0 0.0 0.0 71.4 0.0 100.0 DecPct: 1869 0.0 0.0 34.5 65.5 0.0 0.0 0.0 0.0 0.0 0.0 100.0 DecPct: 1879 0.0 0.0 20.4 55.1 6.1 18.4 0.0 0.0 0.0 0.0 100.0 DecPct: 1889 2.6 0.0 5.2 48.1 19.5 20.8 0.0 0.0 3.9 0.0 100.0 DecPct: 1899 9.1 0.0 3.0 24.2 16.4 21.2 0.0 0.0 20.6 5.5 100.0 DecPct: 1909 19.6 6.6 5.3 18.0 11.4 18.3 4.8 0.0 13.3 2.7 100.0 DecPct: 1919 19.1 8.5 4.3 16.8 9.8 18.1 4.7 1.7 14.9 2.1 100.0 DecPct: 1929 17.8 8.1 4.0 16.2 10.1 17.8 6.1 2.0 16.0 2.0 100.0 DecPct: 1939 10.9 8.3 13.3 21.1 14.0 9.2 5.1 3.3 13.8 1.1 100.0 DecPct: 1949 8.9 6.1 12.6 19.7 17.9 8.4 5.8 3.2 16.7 0.8 100.0 DecPct: 1959 4.9 4.6 7.8 17.6 12.1 8.7 10.0 5.9 23.5 4.9 100.0 DecPct: 1969 4.6 5.3 4.6 14.6 11.2 9.2 8.3 8.5 29.4 4.4 100.0 DecPct: 1979 4.5 5.2 4.9 13.5 11.7 9.7 8.3 7.9 29.9 4.6 100.0 DecPct: 1989 4.6 5.9 5.4 14.9 11.4 9.5 9.3 6.8 27.7 4.5 100.0 DecPct: 1999 4.2 7.1 6.0 17.0 12.0 8.4 5.9 4.5 28.9 5.9 100.0 DecPct: 2009 3.5 6.9 6.1 18.3 12.3 8.1 5.9 4.0 28.5 6.5 100.0 For COUNTRY CODE: 3
What does it look like in South America minus Brazil? We still have the first thermometer jump, the Patagonia Bubble, and the tropical growth. But after the early 1950s, we get fairly good stability (up to that Venzuelan latitude bump in the 1990s at the expense of the above 20 S to 10 S range.
Look at ./Lats/Therm.by.lat3-303.Dec.LAT (Y/N)? y Year SP -50 -40 -35 -30 -25 -20 -15 -10 10 -NP DecPct: 1849 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 100.0 DecPct: 1859 0.0 0.0 0.0 28.6 0.0 0.0 0.0 0.0 71.4 0.0 100.0 DecPct: 1869 0.0 0.0 34.5 65.5 0.0 0.0 0.0 0.0 0.0 0.0 100.0 DecPct: 1879 0.0 0.0 25.0 67.5 7.5 0.0 0.0 0.0 0.0 0.0 100.0 DecPct: 1889 3.6 0.0 7.1 66.1 17.9 0.0 0.0 0.0 5.4 0.0 100.0 DecPct: 1899 13.4 0.0 4.5 35.7 15.2 0.0 0.0 0.0 23.2 8.0 100.0 DecPct: 1909 25.6 8.7 6.9 23.5 11.4 10.0 0.0 0.0 10.4 3.5 100.0 DecPct: 1919 25.8 11.5 5.7 22.6 10.9 12.9 0.6 0.0 7.2 2.9 100.0 DecPct: 1929 24.1 11.0 5.5 21.9 11.0 13.2 2.7 0.0 7.9 2.7 100.0 DecPct: 1939 13.1 10.1 16.1 25.5 15.7 6.2 3.6 1.5 6.9 1.3 100.0 DecPct: 1949 10.9 7.4 15.4 24.0 20.0 4.7 4.9 1.8 10.1 0.9 100.0 DecPct: 1959 5.7 5.3 9.0 20.0 12.8 6.5 9.2 5.1 20.7 5.6 100.0 DecPct: 1969 5.4 6.2 5.4 16.8 10.8 7.9 7.1 8.1 27.1 5.2 100.0 DecPct: 1979 5.2 6.1 5.7 15.5 11.4 8.3 6.9 7.6 27.8 5.3 100.0 DecPct: 1989 5.6 7.2 6.5 17.6 12.1 7.6 7.3 6.3 24.5 5.4 100.0 DecPct: 1999 5.3 8.8 7.5 20.6 13.0 7.0 2.6 3.2 24.7 7.3 100.0 DecPct: 2009 4.4 8.8 7.8 22.6 13.5 7.4 2.0 2.2 23.0 8.3 100.0 For COUNTRY CODE: 3 minus 303 Look at ./Lats/Therm.by.lat3-303.per.LAT (Y/N)?
Not the greatest, but livable.
So what changed between 1989 and 2009? A lot, but I don’t know exactly what to make of it. Here are the station changes. Leading – means deleted, + means added. The only thing that really jumps out at me is the number of very high altitude stations being dropped. That third number, after the LAT and LONG, is the altitude in meters.
[chiefio@tubularbells analysis]$ cat 303-3.diff.1989-2009 - 30187065000 RIVADAVIA -24.17 -62.90 205 205R -9FLMAno-9x-9SUCCULENT THORNSA 0 - 30187149000 PRESIDENCIA R -26.82 -60.45 92 90S 49FLxxno-9x-9SUCCULENT THORNSC 16 - 30187166000 CORRIENTES AE -27.45 -58.77 62 60U 180FLxxno-9A 3SEMIARID WOODS C 36 - 30187322000 CHEPES -31.33 -66.60 658 818R -9HIxxno-9A-9SUCCULENT THORNSB 12 - 30187582000 AEROPARQUE -34.60 -58.50 6 21U 9927FLxxCO 4x-9WARM CROPS C 95 - 30187585000 BUENOS AIRES -34.58 -58.48 25 21U 9927FLxxCO 4x-9WARM CROPS C 92 - 30187596000 PUNTA INDIO B -35.37 -57.28 22 30R -9FLxxCO10A-9WATER A 0 - 30187623001 GENERAL ACHA -37.40 -64.60 230 262R -9FLDEno-9A-9WARM GRASS/SHRUBA 0 - 30187642000 AZUL AERO -36.75 -59.83 132 103S 44FLxxno-9A 3WARM CROPS C 26 - 30187679000 PIGUE AERO -37.60 -62.38 304 275S 10HIxxno-9A 1WARM CROPS B 23 - 30187774000 MAQUINCHAO -41.25 -68.73 888 880R -9HIDEno-9A-9COOL DESERT A 0 - 30187814000 PASO DEL LOS INDIOS -43.82 -68.88 460 -999R -9HIDEno-9x-9WATER A 0 - 30187880000 GOBERNADOR GR -48.78 -70.17 357 408R -9HIDEno-9A-9COOL DESERT A 0 - 30187903000 LAGO ARGENTIN -50.33 -72.30 220 224R -9MVxxLA-9A-9WARM MIXED B 0 - 30187912000 SANTA CRUZ AE -50.02 -68.57 111 72R -9HIxxCO10A-9COOL DESERT A 0 - 30285041000 COBIJA -11.03 -68.78 235 275R -9HIxxno-9A-9TROP. SEASONAL A 10 - 30285043000 RIBERALTA -11.00 -66.12 141 158R -9HIxxno-9A-9TROP. SEASONAL A 0 - 30285104000 SAN JOAQUIN -13.07 -64.82 140 200R -9HIxxno-9A-9TROP. SAVANNA A 0 - 30285141000 RURRENABAQUE -14.47 -67.57 204 719R -9HIxxno-9A-9TROP. MONTANE A 0 - 30285154000 TRINIDAD -14.82 -64.92 155 210S 20HIxxno-9A 2TROP. SAVANNA C 24 - 30285196000 CONCEPCION -16.15 -62.02 497 404R -9HIxxno-9A-9TROP. SAVANNA A 0 - 30285201000 LA PAZ/ALTO -16.52 -68.18 4038 4040U 635MVxxno-9A 1WARM GRASS/SHRUBC 46 - 30285207000 SAN IGNACIO D -16.38 -60.97 413 422R -9HIMAno-9A-9TROP. SAVANNA C 0 - 30285223000 COCHABAMBA -17.42 -66.18 2548 2744U 204MVxxno-9A 1WARM GRASS/SHRUBC 30 - 30285230000 CHARANA -17.58 -69.60 4054 4098R -9MVxxno-9A-9WARM GRASS/SHRUBA 0 - 30285242000 ORURO -18.05 -67.07 3702 3658U 124HIxxLA-9x-9TUNDRA C 0 - 30285245000 SANTA CRUZ/EL -17.80 -63.18 418 516U 255FLxxno-9x-9TROP. SAVANNA C 63 - 30285247000 SAN JOSE DE -17.80 -60.73 284 400R -9HIMAno-9A-9SUCCULENT THORNSA 0 - 30285268000 ROBORE -18.32 -59.77 276 508R -9HIxxno-9A-9TROP. SAVANNA B 9 - 30285283000 SUCRE -19.02 -65.27 2903 2718U 64MVxxno-9x-9WARM GRASS/SHRUBC 38 - 30285289000 PUERTO SUAREZ -18.98 -57.82 134 201R -9FLMAno-9A-9TROP. SAVANNA B 0 - 30285315000 CAMIRI -20.00 -63.53 798 1015R -9MVxxno-9A-9SUCCULENT THORNSC 19 - 30285365000 YACUIBA -21.95 -63.65 645 714R -9MVxxno-9x-9SUCCULENT THORNSA 0 - 30485543000 QUINTERO SANT -32.78 -71.52 8 15S 15FLxxCO 1A 1WATER C 17 --- + 30485574000 PUDAHUEL -33.38 -70.78 475 504U 3615MVxxno-9A 5MED. GRAZING C 30 + 30485577000 SANTIAGO Q. N -33.43 -70.68 520 535U 3615MVxxno-9x-9MED. GRAZING C 75 + 30485682000 CONCEPCION -36.77 -73.05 12 41U 206HIxxCO 4A 1WATER C 43 - 30485766000 VALDIVIA -39.62 -73.08 19 147U 116HIxxCO17A25WARM CROPS A 0 - 30485834000 ISLA HUAFO -43.57 -74.83 140 0R -9HIxxCO 1x-9WATER A 0 --- + 30485874000 BALMACEDA -45.92 -71.68 520 903R -9MVxxno-9A-9WARM DECIDUOUS A 0 - 30489057000 BASE ARTURO P -62.50 -59.68 5 4R -9HIICCO 1x-9WATER A 0 - 30580110000 MEDELLIN/OLAY 6.22 -75.60 1499 2121U 1071MVxxno-9A 1WARM FIELD WOODSC 38 - 30580241000 LAS GAVIOTAS 4.55 -70.92 167 203R -9HIxxno-9A-9TROP. SAVANNA A 0 - 30580336001 TUMACO/EL MIRA 1.60 -78.80 5 30R -9FLxxCO10x-9EQ. EVERGREEN A 0 - 30684088002 IZOBAMBA-SANTA CATALINA -0.37 -78.55 3058 3544R -9MVxxno-9x-9WARM GRASS/SHRUBC 9 - 30684132000 NUEVO ROCAFUE -0.92 -75.40 215 160R -9HIFOno-9x-9EQ. EVERGREEN A 0 - 30684135000 PORTO VIEJO-G -1.03 -80.43 44 121U 60HIxxCO25x-9WARM GRASS/SHRUBC 21 - 30684147000 AMBATO/CHACHO -1.20 -78.57 2520 3042U 78MVxxno-9x-9WARM GRASS/SHRUBC 7 - 30684179000 EL PUYO -1.50 -77.95 950 1004R -9MVxxno-9x-9EQ. EVERGREEN A 0 - 30684202001 MILAGRO -2.12 -79.60 13 30R -9FLxxno-9x-9TROPICAL DRY FORC 22 - 30684203000 GUAYAQUIL/SIM -2.15 -79.88 9 24U 823HIxxCO30A 1TROPICAL DRY FORC 59 - 30684226000 CANAR -2.55 -78.93 3120 3290R -9MVxxno-9x-9TROP. MONTANE B 9 - 30781001000 GEORGETOWN 6.80 -58.15 2 0U 63FLxxCO 2x-9MARSH, SWAMP C 20 - 30781002000 TIMEHRI 6.50 -58.25 30 51R -9FLxxno-9A-9COOL CROPS B 0 --- + 30886065000 PRATS-GIL -22.70 -61.50 220 224R -9FLxxno-9A-9SUCCULENT THORNSA 0 - 30886223000 CARAPEGUA -25.80 -57.22 116 146R -9HIxxno-9x-9TROPICAL DRY FORA 0 - 30886248000 PUERTO STROESSNER PARAGUA -25.53 -54.60 196 148U 94FLxxno-9x-9TROP. SEASONAL C 40 - 30984390000 TALARA -4.57 -81.25 90 55U 55HIxxCO 3A 1WARM IRRIGATED C 20 - 30984425000 YURIMAGUAS -5.90 -76.08 184 142R -9FLFOno-9A-9EQ. EVERGREEN A 0 - 30984444000 CHACHAPOYAS -6.22 -77.83 2435 2126R -9MVxxno-9A-9EQ. EVERGREEN B 0 - 30984472000 CAJAMARCA -7.13 -78.47 2622 3213R -9MVxxno-9A-9WARM GRASS/SHRUBC 0 - 30984474000 JUANJUI -7.22 -76.72 363 473R -9MVFOno-9x-9TROP. MONTANE A 0 - 30984531000 CHIMBOTE -9.17 -78.52 21 114U 216MVxxCO 1A10WATER A 0 - 30984534000 TINGO MARIA -9.13 -75.95 665 859R -9MVxxno-9A-9WARM GRASS/SHRUBA 0 - 30984542000 ANTA (HUARAZ) -9.35 -77.60 2760 4064S 45MVxxno-9A20SUCCULENT THORNSA 0 - 30984564000 HUANUCO -9.90 -75.75 1860 3087U 52MVxxno-9A 1WARM GRASS/SHRUBA 0 - 30984658000 PUERTO MALDON -12.63 -69.20 266 210S 13HIxxno-9A 1COOL FOR./FIELD A 0 - 30984673000 AYACUCHO -13.13 -74.22 2749 2775U 69MVxxno-9A 1WARM GRASS/SHRUBC 12 - 30984721000 SAN JUAN -15.38 -75.17 60 63R -9MVxxCO 3A-9WATER A 14 + 31386350000 RIVERA -30.88 -55.53 241 254U 50FLxxno-9x-9WARM GRASS/SHRUBC 32 + 31386430000 PAYSANDU -32.33 -58.03 61 58U 62FLxxno-9x-9WARM GRASS/SHRUBB 27 - 31386460000 PASO DE LOS T -32.80 -56.52 75 91R -9FLxxLA-9x-9WARM GRASS/SHRUBB 13 - 31386490000 MERCEDES -33.25 -58.07 17 30S 35FLxxCO30A 5WARM CROPS B 18 - 31386500000 TREINTA Y TRE -33.22 -54.38 46 79S 26FLxxno-9A 3WARM CROPS B 17 - 31480405000 LA ORCHILA 11.80 -66.18 3 0R -9FLxxCO 1A-9WATER A 0 - 31480407000 MARACAIBO-LA 10.57 -71.73 65 8U 652HIxxCO10A 4TROP. SAVANNA C 20 - 31480416002 CARACAS CAGIGAL OBS VENEZUELA 10.50 -66.90 1042 1135U 1035MVxxCO12x-9WARM CROPS C 107 + 31581401000 SAINT-LAURENT 5.50 -54.03 9 34R -9FLxxCO30x-9EQ. EVERGREEN C 0 + 31581408000 SAINT GEORGES 3.88 -51.80 7 46R -9FLxxno-9x-9EQ. EVERGREEN A 0 + 31581415000 MARIPASOULA 3.63 -54.03 106 268R -9HIxxno-9A-9EQ. EVERGREEN A 0 + 31788903000 GRYTVIKEN, -54.27 -36.50 3 88R -9MVxxCO 1x-9WATER A 0 [chiefio@tubularbells analysis]$
The data format of those records is described here, about 1/2 way down:
https://chiefio.wordpress.com/2009/02/24/ghcn-global-historical-climate-network/
The South American Temperature Series
Same as the others. Year, 12 monthly averages of the daily MIN-MAX average, the average of those daily values over the whole year, and the number of thermometer locations (ignoring modification flag) in use in that year.
After a ramp up in thermometer numbers to about 1950, with the usual latitude and altitude dependent bias in the results, we reach relative stability about 1950. From that point forward, the temperature average runs about 18 C +/- a degree or so. There is some ripple in the data. It is not clear to me if this is from a climate cycle or from geographic variations in thermometer counts due to dropouts from the various revolutions that seem to sweep over South American countries from time to time. Some digging would likely make that more clear.
What is very clear in this data is that CO2 variation rising over time, especially post WWII, does not correlate well with the flat 18C while changes in thermometer locations have a very strong correlation.
Look at ./Temps/Temps.3.minus303.yrs.GAT (Y/N)? y Thermometer Records, Average of Monthly Data and Yearly Average by Year Across Month, with a count of thermometer records in that year -------------------------------------------------------------------------- YEAR JAN FEB MAR APR MAY JUN JULY AUG SEPT OCT NOV DEC YR COUNT -------------------------------------------------------------------------- 1880 22.1 21.5 19.1 15.4 12.6 11.6 10.1 12.4 11.9 14.9 19.2 22.5 16.1 5 1881 21.4 22.6 20.4 15.9 12.4 9.2 8.6 11.4 13.8 16.3 19.2 22.9 16.2 5 1882 22.9 21.8 18.8 14.8 12.4 9.4 9.1 11.9 13.6 18.1 19.0 20.5 16.0 5 1883 22.2 21.5 19.9 15.4 13.0 11.2 10.2 11.0 13.0 16.0 19.0 21.5 16.2 6 1884 23.7 21.9 21.1 15.8 11.0 8.5 9.0 14.4 14.0 15.9 18.9 21.6 16.3 5 1885 22.7 21.3 19.4 14.4 11.5 8.6 7.8 10.7 14.1 16.3 20.1 20.5 15.6 5 1886 23.0 21.5 20.0 15.6 12.5 8.8 9.5 10.9 13.0 15.3 18.5 21.8 15.9 5 1887 22.1 20.8 20.5 17.0 14.2 14.3 13.0 16.2 15.5 17.6 19.9 21.7 17.7 6 1888 22.3 21.5 19.5 16.9 12.6 9.9 12.6 13.4 14.7 16.2 18.2 20.8 16.5 7 1889 20.8 20.3 19.5 15.6 13.8 11.3 10.9 11.0 13.7 16.4 18.8 19.8 16.0 7 1890 19.9 20.4 18.4 17.4 12.4 10.7 11.6 11.3 13.2 16.3 19.8 21.3 16.1 7 1891 19.8 20.6 19.3 17.1 13.7 13.6 13.8 13.8 16.3 17.3 19.7 20.8 17.1 10 1892 20.6 20.2 18.2 16.3 13.7 11.1 12.8 12.6 14.4 16.5 17.9 19.6 16.2 9 1893 19.9 19.2 19.6 16.6 13.8 11.8 15.0 14.6 16.5 17.0 20.6 21.6 17.2 11 1894 21.5 21.4 19.4 17.8 16.1 13.5 13.9 15.0 16.3 17.7 20.1 20.8 17.8 11 1895 20.1 20.7 19.4 17.4 15.4 14.8 13.8 15.0 16.0 16.6 18.3 20.0 17.3 12 1896 20.5 20.6 19.3 17.4 15.6 12.8 14.7 16.0 16.7 18.6 19.2 20.2 17.6 13 1897 21.0 20.8 20.5 17.8 15.3 13.2 11.9 13.3 15.0 17.3 19.6 20.8 17.2 13 1898 20.7 21.5 18.9 16.6 14.7 14.1 12.3 12.7 15.2 16.1 18.1 20.5 16.8 13 1899 20.8 20.1 19.5 17.4 16.2 12.3 14.4 14.0 14.9 16.2 18.1 20.9 17.1 13 1900 21.7 21.4 19.6 17.5 14.6 14.2 15.4 14.0 15.5 16.7 18.5 19.5 17.4 15 1901 19.1 18.2 17.1 14.5 12.8 11.9 10.3 11.1 13.2 14.5 15.5 18.6 14.7 22 1902 18.5 18.8 16.9 15.2 13.0 10.9 9.2 9.4 11.8 13.5 15.6 17.7 14.2 23 1903 17.6 17.6 16.6 14.1 12.3 10.4 9.6 10.3 12.5 13.3 15.4 16.5 13.8 24 1904 18.4 17.4 16.2 14.9 12.3 10.9 9.7 10.7 12.9 13.6 15.6 17.0 14.1 25 1905 16.7 15.8 15.7 13.1 10.2 8.9 7.3 9.0 10.9 12.4 14.2 15.0 12.4 26 1906 17.2 17.1 15.6 13.4 10.6 7.8 8.4 9.7 10.8 13.0 14.5 15.3 12.8 27 1907 16.7 17.3 15.1 12.6 10.3 8.1 8.5 8.0 9.9 12.2 14.4 15.1 12.3 26 1908 16.6 16.6 15.8 12.3 9.3 9.0 8.3 8.6 10.8 11.8 13.9 15.0 12.3 25 1909 17.0 15.7 15.2 13.2 9.9 8.6 8.5 9.9 11.0 12.8 13.9 15.5 12.6 27 1910 16.2 15.8 14.4 12.2 10.5 8.7 7.7 9.2 10.4 12.4 14.5 15.6 12.3 28 1911 16.2 15.8 14.6 12.1 10.7 8.1 8.2 8.0 9.5 11.6 13.1 15.0 11.9 27 1912 16.6 15.9 15.0 12.5 9.6 8.3 7.5 7.8 10.4 12.5 13.1 15.5 12.1 27 1913 16.4 16.4 14.5 13.0 10.5 8.3 8.8 9.0 11.1 12.4 14.0 15.6 12.5 28 1914 16.9 16.9 15.2 12.5 10.8 8.7 8.6 8.8 10.2 12.2 13.1 15.6 12.5 29 1915 16.1 16.5 15.2 12.7 10.6 7.6 9.0 9.2 11.0 12.6 14.8 16.0 12.6 30 1916 17.0 16.5 14.5 13.6 11.1 7.1 7.2 9.1 11.0 13.0 14.5 15.4 12.5 30 1917 16.8 16.7 15.0 13.3 10.6 9.3 8.4 9.1 10.7 12.8 14.7 16.1 12.8 30 1918 16.5 16.4 15.0 13.2 9.6 8.5 7.9 8.8 10.3 12.6 14.1 16.3 12.4 31 1919 17.3 16.5 15.8 12.6 11.6 8.7 8.9 9.0 10.0 11.8 13.1 15.9 12.6 30 1920 16.7 16.3 15.3 13.7 11.0 8.4 8.0 9.8 11.3 12.0 14.0 15.8 12.7 29 1921 16.3 16.1 14.9 13.3 11.0 8.0 8.2 9.0 10.7 12.7 14.1 15.9 12.5 30 1922 16.5 16.3 15.0 13.1 10.8 7.9 9.6 9.4 11.3 12.2 14.5 15.7 12.7 31 1923 16.2 16.5 15.3 12.8 10.1 8.8 7.0 8.5 10.6 11.5 14.0 14.9 12.2 31 1924 16.5 15.8 15.3 12.5 10.0 9.0 7.8 8.6 10.3 13.0 13.9 16.0 12.4 31 1925 16.4 16.5 15.6 13.0 10.3 8.3 8.1 9.7 10.1 12.4 14.7 16.4 12.6 31 1926 16.8 17.2 15.8 12.8 10.6 9.1 8.3 9.8 10.7 12.3 14.6 16.1 12.8 31 1927 16.5 17.0 15.6 13.3 10.6 8.4 8.3 9.2 10.1 12.5 14.2 15.3 12.6 31 1928 16.1 15.7 15.1 13.1 10.2 7.8 8.2 9.3 10.8 12.5 14.5 15.0 12.4 31 1929 16.3 16.3 14.7 13.5 10.1 8.4 8.7 8.7 10.8 12.4 14.4 15.2 12.5 30 1930 16.3 16.2 14.5 13.0 10.3 8.8 7.0 7.5 10.7 11.4 14.3 15.9 12.2 29 1931 19.7 19.9 17.8 14.5 10.1 8.9 8.9 10.2 11.3 15.5 15.8 19.2 14.3 72 1932 20.6 19.6 18.2 15.0 11.2 9.5 10.6 9.7 12.6 15.1 17.9 18.9 14.9 72 1933 19.7 19.3 17.6 15.4 12.7 9.7 8.2 11.3 12.7 15.3 17.2 18.6 14.8 76 1934 21.0 18.5 17.8 13.8 12.0 9.9 9.5 10.8 11.9 14.5 16.4 18.5 14.6 75 1935 19.8 19.6 19.1 14.5 13.8 10.5 9.0 10.7 11.5 13.3 17.6 18.8 14.9 75 1936 19.9 19.4 18.0 15.4 12.0 9.9 10.2 9.8 12.7 15.2 17.1 19.3 14.9 75 1937 20.1 20.1 17.7 15.2 11.9 11.1 9.4 10.8 12.6 14.1 17.1 19.2 14.9 75 1938 19.1 19.4 17.3 13.9 12.5 10.1 9.5 9.6 12.8 15.3 17.3 19.7 14.7 75 1939 20.6 19.2 17.4 13.9 12.4 10.9 10.3 11.7 12.5 15.2 16.1 18.1 14.9 76 1940 19.8 19.7 17.7 15.1 13.4 11.1 11.1 10.3 12.8 13.9 16.9 18.9 15.1 77 1941 20.1 18.9 17.2 14.6 11.9 10.5 10.5 11.6 11.4 15.9 16.9 18.9 14.9 91 1942 20.7 20.0 17.4 15.2 11.5 8.8 8.6 11.1 13.0 14.9 18.0 20.0 14.9 91 1943 20.9 20.7 17.8 15.5 13.3 11.1 11.2 9.7 13.4 16.0 16.8 19.6 15.5 94 1944 19.7 20.3 18.4 15.6 13.2 11.0 11.0 12.1 14.7 15.8 17.5 20.4 15.8 93 1945 20.9 20.0 18.3 16.2 13.1 10.2 9.9 12.6 13.6 16.3 16.9 18.9 15.6 95 1946 19.3 19.8 17.5 15.9 12.8 10.0 10.0 11.4 13.6 15.1 17.7 18.6 15.1 95 1947 19.9 19.6 17.8 14.9 12.5 11.5 9.4 10.3 12.5 15.1 18.0 18.6 15.0 93 1948 20.5 19.4 17.1 15.0 12.6 11.2 9.6 9.7 13.6 15.3 17.5 20.8 15.2 89 1949 20.3 19.8 18.3 16.3 13.6 11.7 10.6 11.6 13.0 14.9 18.4 19.6 15.7 101 1950 20.4 20.8 19.1 16.8 14.2 12.1 11.3 12.2 13.3 15.4 17.6 19.8 16.1 108 1951 21.4 20.3 19.8 17.9 17.2 15.1 15.4 15.9 17.0 18.7 19.9 21.2 18.3 164 1952 22.7 22.1 21.6 18.1 17.0 12.8 14.6 15.2 16.6 18.1 19.7 21.1 18.3 167 1953 21.7 22.2 20.7 18.1 16.4 14.5 12.7 16.2 17.5 17.4 19.9 21.3 18.2 173 1954 21.4 21.6 20.6 18.2 15.0 13.6 13.0 14.6 15.6 17.6 20.0 20.8 17.7 173 1955 22.2 21.4 19.4 17.8 15.6 14.2 12.6 14.6 16.2 17.5 20.5 21.0 17.8 178 1956 20.7 21.0 20.3 17.4 14.8 14.1 14.5 14.9 16.6 18.4 20.1 21.3 17.8 181 1957 22.1 21.2 21.6 18.3 18.1 14.8 13.9 15.7 16.6 18.9 20.0 21.7 18.6 181 1958 22.4 21.9 21.3 19.0 16.4 15.8 16.4 14.8 17.5 19.5 20.4 21.0 18.9 184 1959 21.4 22.0 20.6 17.9 16.1 14.8 15.3 14.8 17.1 18.5 19.9 21.5 18.3 190 1960 22.6 22.3 21.0 18.7 16.1 15.1 14.6 15.6 17.1 18.8 20.2 21.5 18.6 189 1961 22.1 21.4 20.5 18.5 17.5 14.5 14.5 16.6 16.8 19.1 20.3 21.0 18.6 208 1962 21.3 21.4 20.7 18.2 16.2 14.8 13.5 15.7 17.6 18.5 20.7 21.7 18.4 208 1963 21.5 21.5 20.2 19.0 16.9 15.4 15.7 16.3 17.1 18.8 19.2 21.1 18.6 207 1964 21.9 21.4 20.0 18.7 17.1 14.0 14.2 15.4 17.0 18.3 19.3 20.3 18.1 209 1965 21.6 21.5 20.2 18.4 16.5 16.8 14.7 16.3 17.1 19.2 20.3 20.6 18.6 211 1966 21.6 20.5 20.2 18.8 16.8 15.6 14.9 15.0 16.5 18.3 19.9 20.5 18.2 212 1967 21.1 21.1 19.8 18.7 17.7 13.5 14.4 15.4 16.8 18.5 19.7 21.3 18.2 208 1968 21.3 21.1 19.7 17.4 15.6 14.7 15.4 15.9 16.5 18.3 20.8 20.9 18.1 212 1969 21.6 21.6 20.7 19.0 17.4 15.0 15.0 15.1 17.6 18.0 20.1 21.3 18.5 221 1970 21.4 21.5 20.2 19.2 16.5 14.5 14.3 14.8 17.0 18.2 19.1 20.4 18.1 221 1971 20.8 20.4 20.1 17.5 15.8 13.8 15.2 15.7 17.9 18.5 20.6 21.4 18.1 242 1972 21.9 21.6 20.2 18.5 18.1 16.1 15.8 15.4 17.5 18.6 20.2 21.6 18.8 242 1973 22.2 21.9 21.3 19.1 17.0 16.1 14.6 15.2 17.1 18.9 19.7 20.4 18.6 245 1974 21.3 20.6 20.2 18.4 16.7 14.9 15.2 15.3 16.5 18.5 20.2 20.6 18.2 242 1975 21.3 21.0 20.2 18.7 16.8 15.8 14.1 15.2 17.0 18.5 19.5 21.1 18.3 254 1976 21.3 20.9 19.3 18.6 17.4 14.9 14.9 15.3 17.1 19.1 20.3 21.0 18.3 251 1977 21.8 21.5 20.8 19.3 16.6 15.8 15.9 15.9 18.0 19.5 20.1 21.3 18.9 255 1978 21.5 21.5 20.9 18.7 17.0 15.3 16.1 15.4 18.0 19.3 20.4 21.6 18.8 251 1979 22.4 21.9 20.6 18.8 17.3 15.3 16.0 17.5 17.3 19.2 19.9 21.3 19.0 251 1980 22.2 21.8 21.7 19.5 17.7 15.2 14.9 16.0 17.1 19.2 19.8 21.6 18.9 254 1981 21.3 21.6 20.5 19.0 17.4 14.8 14.3 15.6 16.1 18.2 19.8 20.9 18.3 225 1982 21.6 20.6 20.2 18.5 16.6 14.2 13.9 15.8 16.7 18.4 19.4 21.6 18.1 190 1983 22.6 21.6 20.6 18.7 16.3 13.0 12.9 14.0 15.6 18.6 19.9 22.0 18.0 183 1984 21.8 21.5 20.0 17.2 15.7 13.0 13.6 13.5 16.3 18.9 19.5 20.3 17.6 184 1985 21.7 21.7 20.8 18.5 16.7 14.5 14.2 14.6 16.5 18.3 20.2 21.0 18.2 189 1986 22.0 20.8 19.1 18.4 15.6 14.4 13.8 15.2 16.2 17.9 19.4 21.2 17.8 184 1987 22.3 22.1 21.1 19.2 15.2 14.8 15.3 14.6 16.5 18.8 20.7 21.3 18.5 187 1988 22.3 21.8 21.6 18.4 15.5 13.7 13.1 15.1 16.0 18.1 21.0 22.3 18.2 193 1989 22.8 22.5 20.5 18.4 15.7 14.8 13.5 15.6 14.8 18.0 20.1 21.9 18.2 188 1990 22.3 21.5 20.6 18.1 15.6 13.6 15.9 16.2 15.7 18.5 20.5 20.7 18.3 171 1991 22.1 20.9 20.7 17.7 15.8 12.0 12.4 14.5 16.1 16.4 18.9 21.1 17.4 170 1992 22.5 23.7 23.2 16.8 13.8 12.0 13.6 13.2 14.3 16.0 18.0 21.2 17.4 154 1993 21.4 20.6 19.0 15.9 13.8 11.9 12.9 12.4 15.9 18.3 16.3 20.9 16.6 157 1994 21.8 20.3 19.3 16.5 15.8 17.2 12.8 14.9 18.3 16.7 19.5 22.1 17.9 163 1995 21.5 20.8 19.9 18.1 15.6 12.8 14.5 15.0 16.5 17.8 20.4 21.9 17.9 160 1996 21.4 21.1 20.0 18.1 17.1 13.3 13.6 16.1 15.3 18.3 19.3 21.0 17.9 164 1997 22.0 20.5 20.1 18.1 16.5 13.5 13.8 16.3 16.2 18.2 19.1 21.5 18.0 165 1998 21.1 20.1 19.4 18.1 16.5 14.5 14.9 14.7 15.3 19.3 20.7 20.6 17.9 162 1999 21.3 21.5 20.3 16.7 16.6 13.7 13.5 14.9 17.3 17.5 19.2 20.7 17.8 160 2000 22.1 21.1 19.1 17.8 15.7 14.1 12.3 14.9 15.4 18.7 19.2 21.1 17.6 156 2001 21.1 21.8 21.3 17.9 15.5 14.0 14.1 16.4 16.7 18.2 20.0 21.7 18.2 153 2002 21.9 21.1 20.2 17.8 15.4 12.3 13.4 15.0 16.8 18.4 20.1 21.0 17.8 147 2003 22.1 21.5 20.4 18.4 16.2 14.8 14.0 14.0 17.0 19.2 20.1 20.1 18.2 148 2004 22.6 21.7 21.1 18.4 13.8 13.8 13.1 15.5 17.0 18.3 20.7 21.8 18.1 143 2005 22.6 22.3 20.8 18.1 16.2 14.1 14.4 15.5 16.2 18.3 20.3 21.0 18.3 142 2006 22.5 22.3 20.9 18.9 16.1 15.3 16.5 15.7 16.9 19.9 20.3 22.3 19.0 142 2007 22.3 21.9 21.1 18.7 15.1 13.8 12.7 13.6 17.0 18.4 19.1 20.8 17.9 136 2008 22.3 22.1 20.7 18.0 15.7 13.9 15.3 15.4 17.3 19.1 21.6 22.1 18.6 133 21.3 21.0 19.9 17.8 15.7 13.9 13.7 14.6 16.0 17.8 19.4 20.7 17.6 20.3 20.0 18.7 16.3 14.0 12.0 11.9 12.8 14.4 16.2 18.1 19.6 16.2 For Country Code 3 minus 303 [chiefio@tubularbells analysis]$
For comparison, here is the data series for South America as a whole. We can see the warming introduced with Brazil (not a surprise, the Amazon is a warm place) and we can also see the tendency for the Brazilian warming trend from it’s thermometer migration north to show up in these numbers, though the effect is fairly muted. We have the typical expansion of thermometer counts, then a threshold is reached with sufficient numbers to give some stability. That, again, is about 1951 with a 19.1 C annual average. This rises, with that Samba wobble, to 20.2 in 2006. Not much, but the Brazilian thermometer changes show through.
Look at ./Temps/Temps.3.yrs.GAT (Y/N)? y Thermometer Records, Average of Monthly Data and Yearly Average by Year Across Month, with a count of thermometer records in that year -------------------------------------------------------------------------- YEAR JAN FEB MAR APR MAY JUN JULY AUG SEPT OCT NOV DEC YR COUNT -------------------------------------------------------------------------- 1880 22.7 22.3 20.3 16.9 14.3 13.4 12.0 14.2 13.5 16.1 20.0 23.0 17.4 6 1881 22.2 23.1 21.2 17.1 14.0 11.1 10.5 12.7 15.0 17.2 19.8 23.1 17.2 6 1882 23.2 22.2 19.8 16.2 13.9 11.2 10.7 13.2 14.6 18.7 19.5 20.8 17.0 6 1883 22.5 22.0 20.6 16.6 14.2 12.8 11.6 12.3 14.3 16.9 19.7 21.9 17.1 7 1884 23.7 22.3 21.6 17.1 12.7 10.5 10.9 15.7 15.0 16.8 19.6 22.0 17.3 6 1885 22.7 21.8 19.9 16.5 13.8 11.0 10.5 12.4 15.3 16.9 20.6 21.2 16.9 7 1886 23.4 21.7 20.8 17.0 13.6 10.5 10.9 12.0 14.3 16.2 19.1 21.8 16.8 7 1887 22.0 21.4 20.4 17.8 14.9 14.8 13.7 16.1 16.2 18.1 19.7 21.8 18.1 9 1888 21.4 21.6 20.1 17.5 14.1 11.9 13.6 14.7 16.5 18.2 19.4 21.5 17.5 10 1889 21.8 21.4 20.8 17.4 15.3 12.1 12.7 12.5 14.2 17.0 19.3 21.1 17.1 10 1890 20.9 21.1 19.6 17.7 13.9 11.9 12.9 12.7 14.8 16.6 19.4 21.2 16.9 10 1891 20.6 21.1 20.0 17.8 14.7 14.4 14.1 14.3 16.6 17.7 19.7 20.7 17.6 13 1892 21.3 21.0 19.4 17.2 14.4 12.3 13.0 13.4 15.0 16.9 18.3 19.6 16.8 12 1893 20.5 19.6 20.0 17.0 14.5 12.7 14.8 14.4 16.0 16.9 19.9 21.4 17.3 14 1894 22.2 21.8 19.9 18.0 16.2 13.4 14.0 15.2 16.5 18.2 20.0 20.8 18.0 14 1895 20.7 20.9 20.1 17.9 15.9 15.0 14.2 15.4 16.1 17.1 18.8 20.9 17.8 16 1896 21.5 21.8 20.3 18.5 16.7 14.8 15.9 17.2 18.0 19.7 20.5 21.8 18.9 18 1897 22.2 21.7 21.4 19.6 17.3 14.9 13.7 15.3 16.5 18.7 20.5 22.0 18.6 18 1898 22.3 22.6 20.9 18.8 16.6 16.3 14.9 15.2 16.7 17.6 19.6 21.6 18.6 18 1899 21.9 21.3 21.1 18.9 17.6 14.3 16.0 16.2 16.9 18.1 19.8 21.7 18.6 18 1900 22.4 22.2 21.1 18.9 16.8 15.9 17.0 16.0 17.2 18.2 19.8 20.8 18.9 20 1901 20.4 19.6 18.6 16.2 14.6 13.7 12.4 13.4 15.2 16.5 17.2 19.7 16.5 29 1902 19.8 20.2 18.4 16.9 14.9 13.1 11.8 11.7 14.0 15.5 17.6 19.4 16.1 30 1903 19.0 19.2 18.4 15.9 14.2 12.7 11.8 12.5 14.4 15.2 17.0 18.3 15.7 31 1904 19.6 18.9 17.8 16.4 13.9 12.5 11.8 12.6 14.8 15.2 17.2 18.4 15.8 32 1905 18.1 17.5 17.0 14.9 12.5 11.3 9.9 11.5 13.2 14.7 16.1 16.9 14.5 33 1906 18.4 18.2 17.0 15.1 12.6 10.1 10.6 11.9 12.8 14.9 16.3 17.0 14.6 34 1907 18.1 18.7 16.8 14.6 12.2 10.6 10.5 10.6 12.6 14.4 16.4 17.2 14.4 33 1908 18.3 18.3 17.5 14.5 12.1 11.5 11.0 11.0 13.1 14.0 15.9 17.0 14.5 32 1909 18.3 17.6 16.8 15.0 11.9 10.7 10.7 11.9 13.0 14.5 15.6 17.0 14.4 34 1910 18.0 17.5 16.4 14.5 12.5 11.3 10.4 12.0 13.0 14.6 16.4 17.4 14.5 36 1911 17.9 17.6 16.4 14.3 13.0 10.4 10.4 10.6 12.0 14.2 15.8 17.3 14.2 36 1912 18.2 17.7 17.1 15.0 12.7 11.4 10.5 11.2 13.0 15.0 15.8 17.6 14.6 37 1913 18.3 18.3 16.9 15.5 13.1 11.2 11.7 12.0 13.9 15.0 16.5 17.6 15.0 38 1914 18.9 18.8 17.6 15.3 13.5 12.2 12.0 12.1 13.5 15.2 16.0 17.9 15.2 40 1915 18.5 18.8 17.7 15.2 13.9 11.0 12.0 12.6 13.9 15.3 16.9 18.0 15.3 41 1916 18.8 18.4 16.8 15.9 13.8 10.6 10.5 12.2 13.8 15.4 16.8 17.5 15.0 41 1917 18.5 18.3 17.1 15.5 13.0 11.8 11.3 12.0 13.6 15.3 16.9 18.0 15.1 41 1918 18.3 18.1 17.1 15.5 12.6 11.5 10.6 11.7 13.1 15.2 16.5 18.3 14.9 41 1919 18.8 18.3 17.9 14.8 14.5 12.0 12.0 12.1 13.1 14.9 16.0 18.1 15.2 40 1920 18.8 18.4 17.5 16.1 13.6 11.5 11.3 12.6 13.9 15.1 16.7 18.0 15.3 40 1921 18.3 18.2 17.2 15.6 13.7 10.9 11.0 12.2 13.6 15.2 16.4 18.0 15.0 41 1922 18.5 18.3 17.2 15.6 13.5 11.1 12.3 12.5 14.1 14.8 16.7 17.8 15.2 42 1923 18.2 18.4 17.4 15.3 12.8 11.7 10.1 11.7 13.4 14.3 16.4 17.3 14.8 42 1924 18.4 17.9 17.5 15.1 12.8 11.9 10.9 11.6 13.3 15.2 16.1 17.9 14.9 42 1925 18.3 18.4 17.5 15.6 13.1 11.1 10.9 12.7 13.2 14.9 16.8 18.4 15.1 42 1926 18.7 18.9 17.8 15.3 13.2 12.3 11.0 12.8 13.6 15.0 16.7 18.1 15.3 42 1927 18.4 18.7 17.7 15.8 13.3 11.3 11.2 12.2 13.1 15.1 16.7 17.4 15.1 42 1928 18.2 18.0 17.4 15.8 13.1 11.1 11.3 12.2 13.7 15.2 16.8 17.3 15.0 42 1929 18.5 18.3 17.0 15.7 12.8 11.3 11.7 12.0 13.8 15.3 16.7 17.5 15.1 41 1930 18.5 18.4 17.2 15.6 13.4 12.2 10.6 11.3 13.7 14.6 16.9 18.2 15.1 40 1931 20.7 20.8 19.0 16.1 12.2 11.1 11.1 12.3 13.3 16.9 17.2 20.2 15.9 86 1932 21.3 20.5 19.3 16.7 13.1 11.7 12.5 11.7 14.5 16.7 19.1 19.9 16.4 86 1933 20.6 20.2 18.7 16.8 14.2 11.5 10.2 13.0 14.5 16.7 18.2 19.6 16.2 90 1934 21.6 19.5 18.8 15.4 13.8 11.9 11.5 12.8 13.9 16.0 17.8 19.5 16.0 89 1935 20.6 20.4 20.0 15.9 15.1 12.4 11.2 12.7 13.4 14.9 18.6 19.8 16.2 89 1936 20.7 20.3 19.1 16.9 13.9 12.0 12.1 11.8 14.4 16.7 18.3 20.2 16.4 89 1937 20.8 20.9 18.8 16.5 13.5 12.8 11.4 12.8 14.4 15.7 18.3 20.0 16.3 88 1938 19.9 20.2 18.4 15.4 14.1 11.9 11.4 11.6 14.3 16.6 18.4 20.5 16.1 88 1939 21.3 20.1 18.6 15.5 14.2 12.8 12.0 13.4 14.2 16.5 17.4 19.2 16.3 90 1940 20.6 20.5 18.8 16.5 15.0 12.9 12.9 12.3 14.5 15.6 18.1 20.0 16.5 91 1941 21.0 20.1 18.5 16.3 13.8 12.4 12.4 13.5 13.2 17.2 18.2 20.0 16.4 109 1942 21.5 20.9 18.7 16.6 13.3 10.8 10.6 12.9 14.7 16.3 19.1 20.7 16.3 109 1943 21.5 21.4 18.9 16.7 14.7 12.8 12.8 11.6 14.9 17.3 18.0 20.4 16.8 112 1944 20.5 21.0 19.4 16.8 14.7 12.8 12.5 13.7 16.2 17.3 18.6 21.1 17.1 111 1945 21.6 20.8 19.3 17.4 14.4 11.7 11.6 14.2 15.0 17.4 18.0 19.7 16.8 113 1946 20.1 20.7 18.6 17.0 14.4 11.8 11.7 13.1 15.1 16.5 18.8 19.5 16.4 113 1947 20.7 20.5 18.8 16.2 14.2 13.1 11.3 12.0 14.1 16.4 19.0 19.4 16.3 111 1948 21.2 20.4 18.3 16.4 14.2 12.8 11.6 11.6 15.1 16.6 18.6 21.4 16.5 107 1949 21.5 21.0 19.7 17.8 15.5 14.1 13.1 14.0 15.2 16.7 19.5 20.7 17.4 129 1950 21.3 21.8 20.3 18.1 16.1 13.5 13.7 14.6 15.4 17.2 19.1 20.7 17.6 136 1951 21.9 21.1 20.6 18.6 18.0 16.1 16.2 16.8 17.9 19.4 20.6 21.7 19.1 191 1952 23.1 22.6 22.1 18.8 17.7 14.0 15.5 16.3 17.5 19.0 20.4 21.6 19.1 194 1953 22.3 22.6 21.3 18.9 17.3 15.4 13.8 17.1 18.4 18.4 20.5 21.8 19.0 200 1954 22.0 22.1 21.2 18.9 16.0 14.7 14.2 15.5 16.7 18.5 20.5 21.4 18.5 201 1955 22.5 21.8 20.1 18.5 16.4 15.2 13.7 15.5 17.0 18.3 21.0 21.5 18.5 205 1956 21.3 21.4 20.9 18.1 15.7 14.9 15.4 15.8 17.5 19.1 20.5 21.7 18.5 208 1957 22.4 21.7 22.0 18.9 18.7 15.6 14.8 16.5 17.2 19.5 20.6 22.1 19.2 209 1958 22.8 22.4 21.7 19.6 17.0 16.5 17.0 15.7 18.2 20.1 20.9 21.5 19.4 213 1959 21.9 22.3 21.1 18.7 16.9 15.6 16.1 15.6 17.8 19.2 20.4 21.8 19.0 218 1960 22.8 22.6 21.4 19.2 16.7 15.8 15.3 16.3 17.8 19.4 20.7 21.9 19.2 218 1961 22.6 22.0 21.1 19.4 18.3 15.6 15.5 17.6 18.0 19.8 21.0 21.6 19.4 247 1962 21.8 21.9 21.3 19.0 17.1 15.8 14.6 16.7 18.4 19.2 21.3 22.1 19.1 246 1963 22.1 22.0 20.9 19.7 17.7 16.2 16.6 17.2 18.1 19.6 20.0 21.6 19.3 244 1964 22.3 21.9 20.6 19.4 17.8 14.9 14.9 16.2 17.8 18.9 19.8 20.8 18.8 242 1965 22.0 22.0 20.6 19.1 17.2 17.5 15.6 17.1 17.8 19.7 20.8 21.2 19.2 247 1966 22.1 21.1 20.8 19.4 17.3 16.4 15.8 15.8 17.3 19.0 20.5 21.2 18.9 247 1967 21.7 21.7 20.5 19.4 18.6 14.6 15.4 16.4 17.8 19.4 20.4 21.8 19.0 248 1968 21.8 21.5 20.4 18.1 16.3 15.6 16.2 16.7 17.3 19.1 21.3 21.4 18.8 251 1969 22.1 22.1 21.4 19.7 18.2 16.0 15.9 16.1 18.4 18.8 20.7 21.7 19.3 259 1970 21.9 22.1 20.9 19.9 17.4 15.6 15.3 15.9 17.8 18.8 19.7 21.1 18.9 262 1971 21.4 21.0 20.7 18.1 16.6 14.6 16.0 16.4 18.6 19.1 21.0 21.8 18.8 283 1972 22.2 22.0 20.8 19.2 18.8 16.9 16.6 16.4 18.4 19.3 20.8 22.1 19.5 284 1973 22.7 22.5 21.8 19.9 17.9 17.0 15.6 16.1 17.9 19.5 20.2 21.0 19.3 289 1974 21.8 21.2 20.8 19.1 17.6 16.0 16.1 16.4 17.6 19.1 20.7 21.2 19.0 288 1975 21.9 21.7 20.9 19.5 17.6 16.6 15.1 16.3 18.1 19.3 20.1 21.6 19.1 304 1976 21.8 21.4 20.0 19.3 18.2 15.9 15.8 16.3 18.0 19.8 20.8 21.6 19.1 299 1977 22.3 22.0 21.4 19.9 17.4 16.6 16.8 16.8 18.9 20.2 20.8 21.9 19.6 304 1978 22.1 22.0 21.5 19.4 17.8 16.2 17.1 16.3 18.8 20.0 21.0 22.0 19.5 300 1979 22.7 22.4 21.1 19.4 18.0 16.2 16.8 18.3 18.2 20.0 20.5 21.9 19.6 300 1980 22.6 22.2 22.2 20.1 18.5 16.2 15.8 16.9 17.9 19.9 20.4 22.1 19.6 301 1981 22.0 22.3 21.3 19.8 18.4 16.2 15.5 16.9 17.4 19.0 20.8 21.7 19.3 276 1982 22.1 21.3 20.9 19.4 17.8 15.6 15.3 16.7 17.9 19.4 20.5 22.2 19.1 232 1983 23.1 22.3 21.3 19.7 17.6 14.6 14.6 15.7 16.9 19.5 20.7 22.5 19.0 225 1984 22.4 22.4 20.8 18.3 16.7 14.7 15.1 15.1 17.5 20.0 20.4 21.2 18.7 226 1985 22.3 22.3 21.7 19.7 17.8 15.7 15.5 16.0 17.7 19.3 21.0 21.7 19.2 231 1986 22.5 21.6 20.2 19.5 17.1 15.5 15.1 16.6 17.5 19.1 20.4 22.0 18.9 229 1987 22.8 22.7 21.8 20.2 16.7 16.2 16.8 16.4 17.9 20.0 21.6 22.0 19.6 232 1988 22.9 22.6 22.3 19.5 16.6 15.1 14.7 16.4 17.5 19.1 21.6 22.9 19.3 238 1989 23.2 22.9 21.3 19.5 16.9 16.3 14.7 16.8 16.4 19.0 21.0 22.7 19.2 229 1990 22.9 22.2 21.6 19.5 17.0 15.3 17.6 17.3 17.7 19.8 21.6 21.7 19.5 213 1991 22.7 21.8 21.6 19.1 17.8 14.3 14.7 17.3 18.0 18.8 21.0 22.9 19.2 212 1992 23.2 24.3 24.0 18.9 16.6 14.8 15.7 16.0 15.5 18.5 19.5 22.0 19.1 195 1993 22.2 21.6 20.6 18.4 15.3 13.8 14.9 14.4 17.3 19.6 19.9 21.8 18.3 198 1994 22.4 21.6 20.3 18.4 16.7 18.1 14.6 16.1 19.6 18.2 20.2 22.4 19.1 203 1995 22.3 21.3 20.8 19.0 16.9 14.4 16.6 16.2 17.9 18.9 21.1 22.5 19.0 198 1996 22.1 21.8 20.9 19.3 18.0 14.7 15.2 17.6 17.2 19.4 20.6 21.5 19.0 203 1997 22.7 21.3 21.0 19.1 17.7 16.0 16.1 18.1 18.1 19.6 20.8 22.6 19.4 203 1998 22.2 21.7 20.6 19.7 17.7 16.4 16.6 16.8 17.5 20.5 21.8 21.6 19.4 201 1999 22.1 22.4 21.2 18.5 17.6 15.6 15.4 16.9 18.9 19.5 20.7 21.7 19.2 198 2000 23.0 22.2 20.5 19.5 17.8 15.9 14.2 16.5 17.0 19.9 20.4 22.1 19.1 196 2001 22.2 22.8 22.2 19.6 17.4 16.0 16.1 18.0 18.6 19.9 21.5 22.7 19.8 193 2002 22.9 22.2 21.6 19.7 17.6 14.8 15.4 17.3 18.7 20.1 21.4 22.1 19.5 186 2003 23.0 22.4 21.7 19.9 17.9 16.9 16.2 16.3 18.6 20.6 21.4 21.6 19.7 187 2004 23.2 22.5 22.2 20.2 16.1 16.0 15.3 17.3 18.7 20.3 21.9 22.7 19.7 182 2005 23.4 23.2 21.8 19.6 17.9 16.3 16.3 17.5 18.1 20.1 21.5 22.2 19.8 181 2006 23.2 23.1 22.0 20.2 17.5 16.9 18.2 17.4 18.7 21.3 21.3 23.1 20.2 181 2007 23.2 22.9 22.2 20.3 16.8 15.9 15.0 15.8 19.5 20.1 20.7 22.0 19.5 174 2008 22.9 22.8 21.6 19.3 17.2 15.7 17.0 17.2 18.9 20.7 22.5 23.0 19.9 172 22.0 21.7 20.7 18.8 16.9 15.2 15.0 15.9 17.3 18.8 20.2 21.4 18.7 21.2 20.9 19.9 17.7 15.5 13.8 13.6 14.5 16.0 17.7 19.2 20.6 17.6 For Country Code 3
Here we again see that averaging divergent series simply hides the widespread stability of most of the countries of a region in the error caused by the thermometer location changes in a single large country; and that in thermometers, as in real estate, it’s all about “location location location”…
In Conclusion
What I see in all this is that as long as the “composite instrument” of the collection of thermometers is fairly stable, you can get something useful from it. When the parts start moving, not so much… What I said under the New Zealand posting bears repeating:
And just how do you calibrate this composite instrument with all these comings, going, deletions, migrations, and instrument replacements and recalibration / recorrections? When wars, equipment change, and siting changes dominate the signal, just how do you propose to tease out of it that which is perhaps not even there?
We see general stability in the record and we also see that the major determiners by far of what changes an “average of temperatures” are latitude and thermometer count. Everything else is completely swamped by those two things. There is the potential for an “altitude” signal as well, but that will be for a future investigation.
I see no way to extract useful information about “Global Climate Change” from a temperature series with this much noise in the signal via any kind of averaging process. IMHO, the most reasonable approach is to “stabilize the instrument” by taking individual thermometers (or at most, very closely matched thermometers) and making a trend line for them. Then looking at the collection of those trend lines, individually or in aggregates, to see if there is a composite trend, or perhaps regions of co-trend and anti-trend due to global oscillations like the PDO. (We did see under both the New Zealand and the Antarctic postings that there are regions that seem to move in opposition to the North American temperatures, with a relative drop in 1998 instead of a peak).
This is very helpful to me, both for my effort to characterize GIStemp and its failings and for my ideas about how to produce a more usable and valid “SmithTemp” series.
But it also continues to point out the sheer folly of a “Global Average Temperature” via any method that average temperatures, then looks for trends. All you will find is the trends dominated by thermometer location and number changes.
Yet more confirmation that the whole “Global Warming” issue is settling down to an error in where the parenthesis are placed:
Average(dT/dt) works.
d(average of T)/dt does not.
GIStemp, and all the other serial averagers are guilty of using the second of those two approaches. Yes, they dress it up in lots of “reference station method” and “optimal interpolation” and similar camouflage; but in the end, they still have their parenthesis in the wrong place…
Magnificent work once again, EM, well done! I have done regressions on changes in annual mean T against changes in No. of Met.stations and in [CO2], there is no correlation with the latter, and quite a lot with the former!
Using an older v2.mean file I cataloged high altitude stations world wide. Most of them were culled around 1990. Here is a list of the ones above 3000m that you would need to verify, as it may not be completely accurate or there may be a difference with a newer version of v2.mean:
ALT STATION ID STATION NAME BEG. END
(M)
4670 20555472000 XAINZA 1960 1990
4613 20552908000 WUDAOLIANG 1957 1990
4535 20556004000 TUOTUOHE 1956 1990
4508 20555299000 NAGQU 1954 1990
4338 42572469004 BERTHOUD PASS;CO USA 1963 1985
4302 20555664000 TINGRI 1959 1990
4279 20555228000 SHIQUANHE 1961 1990
4273 20556033000 MADOI 1953 1990
4176 20556021000 QUMARLEB 1956 1990
4068 20556018000 ZADOI 1957 1990
4054 30285230000 CHARANA 1951 1989
4038 30285201000 LA PAZ/ALTO 1918 1989
4024 20556106000 SOG XIAN 1961 1990
3968 20556046000 DARLAG 1956 1990
3950 20556257000 LITANG 1953 1988
3896 20556152000 SERTAR 1961 1990
3874 20556116000 DENGQEN 1954 1990
3861 20555696000 LHUNZE 1959 1990
3837 20555578000 XIGAZE 1955 1990
3827 30984735000 JULIACA 1962 1990
3800 30187400001 CRISTO REDENTOR ARG 1941 1984
3743 42572469008 NIWOT RIDGE D1; CO USA 1951 1989
3729 20556357000 DAOCHENG 1957 1990
3702 30285242000 ORURO 1949 1989
3682 20556029000 YUSHU 1951 1990
3650 20555591000 LHASA 1935 1990
3576 64606730000 JUNGFRAUJOCH 1933 1985
3560 30684088001 COTOPAXI 1961 1991
3500 20556065000 HENAN 1959 1990
3488 20556444000 DEQEN 1953 1990
3459 30187007000 LA QUIACA 1911 1991
3441 20556079000 RUO’ERGAI 1957 1990
3420 70089606000 VOSTOK 1958 1991
3388 30984630002 JAUJA 1961 1981
3361 20552533001 QILIAN TUOLE 1957 1988
3350 30984630001 HUANCAYO/HUAYAO 1952 1977
3307 20556137000 QAMDO 1941 1991
3301 20552754000 GANGCA 1957 1990
3290 20552957000 TONGDE 1954 1990
3249 30984686000 CUZCO 1937 1991
3244 42572462006 WOLF CREEK PASS;CO USA 1958 1989
3204 20556144000 DEGE 1956 1990
3192 20552836000 DULAN 1940 1991
3174 20552713000 DA-QAIDAM 1956 1990
3120 30684226000 CANAR 1961 1991
3109 60311146000 SONNBLICK 1887 1991
3088 20552836001 UULAN CAKA 1956 1988
3062 42574531001 LEADVILLE;CO USA 1908 1979
3058 30684088002 IZOBAMBA-SANTA CAT 1975 1990
3049 20556385000 EMEI SHAN 1951 1990
3044 20552787000 WUSHAOLING 1951 1990
3018 42572469006 NIWOT RIDGE C1; CO USA 1952 1989
3000 20556312000 NYINGCHI 1954 1990
Let’s try that list again, as your editor is giving me problems:
ALT STATION ID STATION NAME BEG. END
(M)
4670 20555472000 XAINZA 1960 1990
4613 20552908000 WUDAOLIANG 1957 1990
4535 20556004000 TUOTUOHE 1956 1990
4508 20555299000 NAGQU 1954 1990
4338 42572469004 BERTHOUD PASS;CO USA 1963 1985
4302 20555664000 TINGRI 1959 1990
4279 20555228000 SHIQUANHE 1961 1990
4273 20556033000 MADOI 1953 1990
4176 20556021000 QUMARLEB 1956 1990
4068 20556018000 ZADOI 1957 1990
4054 30285230000 CHARANA 1951 1989
4038 30285201000 LA PAZ/ALTO 1918 1989
4024 20556106000 SOG XIAN 1961 1990
3968 20556046000 DARLAG 1956 1990
3950 20556257000 LITANG 1953 1988
3896 20556152000 SERTAR 1961 1990
3874 20556116000 DENGQEN 1954 1990
3861 20555696000 LHUNZE 1959 1990
3837 20555578000 XIGAZE 1955 1990
3827 30984735000 JULIACA 1962 1990
3800 30187400001 CRISTO REDENTOR ARGENTINA 1941 1984
3743 42572469008 NIWOT RIDGE D1; CO USA 1951 1989
3729 20556357000 DAOCHENG 1957 1990
3702 30285242000 ORURO 1949 1989
3682 20556029000 YUSHU 1951 1990
3650 20555591000 LHASA 1935 1990
3576 64606730000 JUNGFRAUJOCH 1933 1985
3560 30684088001 COTOPAXI 1961 1991
3500 20556065000 HENAN 1959 1990
3488 20556444000 DEQEN 1953 1990
3459 30187007000 LA QUIACA 1911 1991
3441 20556079000 RUO’ERGAI 1957 1990
3420 70089606000 VOSTOK 1958 1991
3388 30984630002 JAUJA 1961 1981
3361 20552533001 QILIAN TUOLE 1957 1988
3350 30984630001 HUANCAYO/HUAYAO 1952 1977
3307 20556137000 QAMDO 1941 1991
3301 20552754000 GANGCA 1957 1990
3290 20552957000 TONGDE 1954 1990
3249 30984686000 CUZCO 1937 1991
3244 42572462006 WOLF CREEK PASS;CO USA 1958 1989
3204 20556144000 DEGE 1956 1990
3192 20552836000 DULAN 1940 1991
3174 20552713000 DA-QAIDAM 1956 1990
3120 30684226000 CANAR 1961 1991
3109 60311146000 SONNBLICK 1887 1991
3088 20552836001 UULAN CAKA 1956 1988
3062 42574531001 LEADVILLE;CO USA 1908 1979
3058 30684088002 IZOBAMBA-SANTA CATALINA 1975 1990
3049 20556385000 EMEI SHAN 1951 1990
3044 20552787000 WUSHAOLING 1951 1990
3018 42572469006 NIWOT RIDGE C1; CO USA 1952 1989
3000 20556312000 NYINGCHI 1954 1990
Sorry. Email me if you want me to send you a file.
WordPress can be a pain some times, but it’s free…
To maintain formatting, you need put LESSTHAN pre GREATERTHAN which starts a fixed format block. You end the block with LESSTHAN SLASH pre GREATERTHAN.
It also steals LT and GT symbols and sometimes the stuff in between them as it tries to turn them into HTML tags…
I’ll spot check the ones you posted against some v2.mean files I have and see if I need a file sent.