GHCN v1 v2 v3 All Data

There’s something interesting in the GHCN v1 vs v2 vs V3 data. I’m not sure exactly what to make of it yet, but I think it matters.

It is my working hypothesis that it indicates the change in nature and placement of thermometers between the series and that it indicates “where to look’ for ‘issues’.

The basic problem that I see in how a Global Average Temperature is calculated is that the data are very poorly suited to the task. There are huge variations in placement of thermometers over time, and over space. The actual instruments change radically and the technology used has tranches by time. As a calorimetry experiment (measuring heat gain / loss) it violates substantially all the standards of acceptable practice. ( I can still remember my chemistry teacher lecturing about the essential need to never change the thermometers … nor move them.)

What I do as a first step is just “look at the shape of the data”. There is no attempt to “fix it” via things like anomaly processing or grid /box apportionment. Why do this? It tells you how big a problem you have. If you don’t know how much problem you are expecting those processes to fix, you have no real basis for assessing their “fitness for use” in removing that problem. In the case of a Global Average Temperature (GAT) we’re supposed to be highly worried about temperatures that vary in the range of 2/10 C to 5/10 C and absolutely panic over 1 C. Yet the data have far more than that variation just from data set to data set (and more between years and geographies even within the same grid / box). So we are expecting those “gridding” and “grid anomaly” processes to fix rather a lot.

(It is worth reminding folks that the “anomaly” formation process is NOT done on individual temperatures from individual instruments in GIStemp. Temperatures are carried AS temperatures through a large number of processes, including the “QA process” and the infilling / homogenizing steps. Only at the bitter end, when making Grid / Box values, is a Grid-Box Anomaly calculated. So no, using “anomalies” does not “fix” the issue, as it is done too late in the process. I have some code, the Dt/dt code, that does anomalies as the very first step, only on an instrument against itself. That code is the next step to run on my ‘to do’ list.)

With that, back at the comparison.

In this pass we are just looking at how much the basic data shift between these data sets. Is there enough ‘shifting’ here to be worried? Might it indicate an issue that the GIStemp and HADcrut code might fail to fully ‘correct’ out? If, for example, we find the data warmed by 1/2 C in winter between v1 and v3, what assurances do we have that the various GAT creating processes can adequately remove that effect perfectly? Yes, perfectly. For the simple reason that if it is not perfect, then some of the “Global Warming” is due to imperfection in the GAT codes. IFF they fail to remove it at all, then we get 1/2 C of “winter global warming” that is in fact an artifact of the changed data sets. Perhaps even more as the data shift dramatically in location and average temperatures over the years within a given data set.

Comparing the Averages of Averages

The code I run takes each year and averages all the readings in any given month for any given collection of instruments. In this case I said to select all instruments that start with any digit between 0 and 7 in the “Country Code”. That’s basically everything other than “ships at sea” I then calculate an “Annual Average” from those data and keep two running totals.

One running total, the AA, is the Average of Monthly Averages. Each monthly value has the same weight. Doesn’t matter if there is only one thermometer in that month, or 5000. This is somewhat overly influenced by the very early thermometers as they get to have a larger implact, being fewer of them. (Yet we are expecting the GAT codes to remove that effect… so it DOES matter.)

The other running total, the Ad, is the Average of Data items. Each individual thermometer reading has the same weight. This is somewhat over influenced by later data simply because we have so much more of it in later years. Still, it will tend to indicate if one version of the data has shifted significantly when compared to another, especially in those years where we have the most data and care the most (since about 1950).

GHCN v1 v2 v3 AA Ad Chart

GHCN v1 v2 v3 AA Ad Chart

What I find particularly interesting about this chart is that it shows how the data themselves have shifted to warmer winters from data set to data set. Even the v2 vs v3 that have almost the same time coverage (2009 to 2012 being the added years in v3). The changes simply must be caused by the changed processing and which thermometers are included in the set, as the small number of added readings are insufficient to shift the averages this much.

We can clearly see that the AA values have a much warmer winter from data set to data set. Interesting to note is that from v1 to v2 the summers COOLED, then in v3 that is “fixed” and the summers are warmed a bit from v2 (though still cooler than in v1).

For the Ad values, the effect is more muted. This implies that the effect may be stronger in earlier years where there are fewer thermometers. Yet we expect the various GAT codes to do exactly that comparison. Few in the past against more in the present. And perfectly remove this bias.

How big is the bias? Just about the same as the supposed Global Warming magnitude.

Here are the data themselves, so you can do individual comparisons:

	Jan	Feb	Mar	Apr	May	June	July	Aug	Sept	Oct	Nov	Dec	Total
v1 AA	2.0	3.4	7.1	11.7	15.9	19.4	21.4	20.8	17.7	13.1	7.6	3.4	12.0
v2 AA	2.5	3.9	7.3	11.8	15.8	18.9	20.8	20.3	17.4	13.1	7.9	3.9	12.0
v3 AA	3.5	4.8	8.2	12.4	16.2	19.2	21.1	20.7	17.9	13.7	8.8	4.8	12.6
													
v1 Ad	0.0	1.4	4.7	9.6	14.3	18.0	19.9	19.2	15.9	10.8	5.4	1.6	10.1
v2 Ad	0.2	1.6	4.8	9.6	14.1	17.7	19.6	19.0	15.8	10.8	5.6	1.9	10.1
v3 Ad	0.7	2.1	5.2	9.8	14.2	17.7	19.5	19.0	15.8	11.0	5.9	2.3	10.3

I find it interesting that the AA change for v1 vs v2 overall was nil, yet by v3 it is 6/10 C. The total change in the data is “only” 3/10 C (but it is the changes averaged within months and years that must be removed by the GAT codes). Still, this indicates that overall the data set has warmed, and that the warmth is distributed in such a way as to have a stronger effect over time.

That the AA values are all higher than the Ad values is interesting. It implies that much of the data are relatively cooler than the averages, and that the cooler data get ‘submerged’ in an average. Odd thing, that. I likely need to chase down what it means but don’t have a working theory at present.

Looking at Jan, for example, we see that the AA changes from 2.0 to 2.5 to 3.5 C between the data sets. We have 1/2 C of “warmer January Averages” between v1 and v2, and a full 1 Degree C between v2 and v3 (for a whopping 1.5 C overall from v1 to v3).

We are expecting the GAT codes (like GIStemp and HADcrut) to succeed at removing 1.5 C of “change from shifting data sets” while finding 1/2 C of “signal” and do so without error.

Looking at July and August, we find the AA changes are “different”. A drop of 0.6 from v1 to v2 and then a rise by 0.3 from v2 to v3, leaving v3 at 0.3 below v1. For August, v3 ends up within 1/10 of v1. For the Ad values, August cools by 2/10 from v1 to either v2 or v3, while July cools by 0.3 to 0.4 C.

So we are expecting these codes to take 1.5 C of warming winters and 1/2 C of cooling summers from changes of data set and manage to not find 1 C of average warming in the data from those changes of instruments.

My question becomes pretty simple:

If we don’t have any stability in the instruments in use, such that we have whole degree and more wandering in the basic data from set to set (and up to several degrees from year to year), just how do we know we are finding tenths of a degree of influence from other effects?

I’d also question just how much ‘global warming’ is actually making things hotter. In the data itself, the only visible effect is a “less brutal winter” and maybe a bit of “nicer summers”. Oh, I supposed one could argue that we need to do the whole ‘anomaly grid / box’ thing before making that assertion… except that the data are of that pattern. So we have to ask the same question about “less brutal winters” as about the GAT creation: How do we know those conversion codes will do a perfect job?

Who has shown that their vetted and proven error bars are less than 1/10 C (that’s 20% of the 1/2 C we are supposed to be worried over, so a generous error target. Yet we have NO evidence at all that the error bars are inside that bounds. There are no published QA tests or validation suites for GIStemp…) There are 2 basic paths from this point: The data are saying something that matters which can be seen in the data (and that is not much absolute warming highly concentrated in winter – most of the data are from the N. Hemisphere so we can make that assertion) or we trust the GIStemp and HADcrut codes to perfectly remove bias in the data that swamps the signal being sought by a factor of 10. (Whole degrees vs tenths).

As there are no published test suite results on GIStemp and HADcrut, if we choose to trust them it is entirely a matter of faith in the codes and nothing more. There are no test suits. There are no “red data” or “pink data” or “white data” tests. There are no stress tests. We could be looking at nothing but the product of computer programming bugs.

That’s the choice as I see it. Blind faith in perfection in computer programming, or concern that the variation in what is supposed to be “the same time series” clearly swamps any signal and even minor errors in the code could leak 1/10th of that noise and result in a false “Global Warming” signal.

The Raw Reports

The rest of this posting is just the raw reports run on the data sets. So folks who wish to play with it can do things like, oh, graph the changes of JAN monthly averages over time…

v1

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
--------------------------------------------------------------------------
1701 -4.2 -1.5  1.6-99.0-99.0 15.4 18.9 15.8-99.0-99.0-99.0 -0.5  6.5    1
1702  2.0 -0.5  0.6  2.6 10.9 16.0 16.0 15.8 10.1  7.5  0.2  0.6  6.8    1
1703 -2.8 -0.9  0.6  7.7 14.1 16.1 15.4 16.3 11.4  6.1  2.2  2.5  7.4    1
1704 -4.9 -0.5  3.9  9.4 11.8 14.1 17.1-99.0-99.0-99.0-99.0 -0.9  6.2    1
1705 -7.1-99.0  1.0-99.0-99.0 16.0 18.3 17.8  8.7  7.5  0.7  1.8  7.2    1
1706 -1.2 -1.0  2.8  7.4 12.8 17.2 16.6 15.6 11.8  8.5  3.5  2.5  8.0    2
1707 -0.5  0.8  2.4  6.4 11.7 17.2 18.0 15.6 12.6  6.0  3.8  1.7  8.0    2
1708  3.0  0.9  4.7  7.7 11.1 14.3 13.7 17.9 14.3  4.6  3.3 -1.6  7.8    2
1709 -9.0 -3.9  0.9  9.4 11.7 16.7 16.0 16.0 12.2  8.1  5.6  2.0  7.1    2
1710 -1.1 -0.2  4.1  6.9 12.9 15.2 15.2 16.5 13.8  9.4  7.4  6.5  8.9    2
1711  3.5  0.0  4.7  9.5 12.2 16.9 16.0 15.6 13.3  9.3  6.5  1.5  9.1    2
1712  0.2  2.9  4.1  7.7 12.3 16.3 16.8 14.9 13.1  9.5  5.0  4.2  8.9    2
1713 -0.3  5.0  1.0  5.3 10.5 13.6 14.8 15.4 13.9  9.3  3.4  2.5  7.9    2
1714  1.9  3.8  5.0  7.9 10.2 14.5 18.5 13.8 13.0  9.7  4.6  2.4  8.8    2
1715  0.7  3.5  5.7  9.6 11.6 14.5 15.8 17.0 14.1 10.3  6.3 -1.5  9.0    2
1716 -5.0  1.5  3.3  9.1 11.3 14.0 16.3 15.5 12.4  8.3  3.9  1.2  7.7    2
1717  0.9  0.7  3.4  7.2 10.2 15.3 15.7 15.5 13.9  9.3  3.4  3.5  8.3    2
1718 -1.6 -0.8  4.6  8.3 12.7 16.0 18.0 19.0 15.1  8.9  5.2  3.3  9.1    2
1719  0.5  2.5  3.5  5.6 13.4 16.0 20.1 18.9 14.1  8.2  5.0  1.3  9.1    2
1720  2.9  2.9  3.1  6.8 12.3 12.6 17.2 14.5 14.3  8.1  5.6  3.6  8.7    2
1721  3.5  0.1  0.8  8.9 10.2 15.3 15.2 16.5 14.4  8.6  5.8  1.9  8.4    2
1722  0.9  3.9  5.5  8.6 11.5 15.1 15.8 15.5 14.6 10.4  6.8  3.3  9.3    2
1723  0.3  2.5  6.4  8.4 12.4 15.6 15.6 15.9 13.9 11.0  2.2  4.7  9.1    2
1724  4.8  3.6  3.7  6.7 11.8 16.7 15.1 16.9 14.2  8.3  5.1  2.0  9.1    2
1725  2.3  0.4  3.5  7.0 10.6 14.0 14.6 14.3 12.5  8.0  3.0  2.0  7.7    2
1726 -1.8  0.2  2.5  7.8 14.1 16.2 15.6 14.4 14.2  9.2  5.3  0.1  8.1    2
1727  2.6  3.6  3.7  7.0 15.0 15.4 16.8 17.5 14.7 11.5  3.6  2.5  9.5    2
1728  2.5 -0.6  6.9  8.9 14.8 16.6 16.5 14.6 13.1  9.2  4.3 -0.6  8.8    2
1729 -3.1  0.3  0.2  6.3 11.1 16.2 17.8 17.7 16.9 12.1  5.3  5.3  8.8    2
1730  2.4  2.3  4.3  9.1 12.6 15.6 17.2 16.8 14.4  7.0  7.5  2.2  9.3    2
1731 -0.5 -0.4  3.3  6.4 12.0 15.3 16.4 16.8 14.8 11.9  6.5  3.2  8.8    2
1732 -0.5  3.3  5.3  9.7 12.9 14.2 16.1 16.2 14.1 10.4  4.4 -0.9  8.8    2
1733  4.3  4.5  5.1 10.5 11.5 13.9 18.3 16.5 12.0  8.2  5.5  5.6  9.7    2
1734  1.6  4.4  6.4  9.5 12.3 14.7 17.0 16.3 14.1  9.5  1.9  1.3  9.1    2
1735  3.0  2.4  5.8  9.6 12.2 15.5 16.1 16.5 15.2  7.5  4.0  3.0  9.2    2
1736  1.3  0.8  3.2  9.2 12.2 15.0 17.3 17.7 13.9  9.3  5.6  4.2  9.1    2
1737  4.0  3.0  5.4  7.3 13.7 16.0 16.6 14.5 14.5  8.7  4.3  2.1  9.2    2
1738  0.0  2.5  5.0  9.6 12.8 15.2 16.5 16.0 13.5  9.9  2.0  4.2  8.9    2
1739 -1.4  0.9  3.6  5.2 12.2 14.8 17.7 14.9 13.8  5.8 -0.9  1.9  7.4    3
1740 -6.3 -5.4  0.5  4.8  7.8 13.2 15.9 15.5 13.8  4.3  1.4  0.5  5.5    3
1741 -2.5  2.3  2.5  5.4  9.4 13.8 17.1 15.7 12.9  9.6  5.8  1.3  7.8    3
1742 -2.8  2.2  1.5  4.9  9.7 14.9 15.9 14.5 10.8  8.0  3.6 -2.5  6.7    3
1743  1.1  1.8  2.6  5.0 12.2 17.8 17.6 16.9 14.2  4.6  4.6  0.2  8.2    5
1744 -3.5 -3.0  0.4  7.0 11.9 16.0 18.2 15.1 13.6  7.9  3.8 -1.1  7.2    5
1745 -3.0 -3.7  0.0  6.8 12.6 16.8 17.8 16.8 15.8  8.5  4.6 -0.4  7.7    5
1746 -0.6 -0.6 -0.9  6.3 13.0 15.5 17.8 15.2 13.1  6.3  1.4  3.0  7.5    5
1747 -1.5 -0.2 -0.5  7.0 11.1 18.3 18.0 15.8 15.0  9.3  4.2  1.0  8.1    5
1748 -1.5 -1.5 -2.3  6.4 13.2 17.3 17.6 18.2 14.0  8.4  4.5  3.4  8.1    5
1749 -0.2 -1.4  0.3  6.4 13.3 15.0 17.1 16.9 13.6  7.6  3.4  0.8  7.7    5
1750 -0.6  1.2  4.3  7.1 11.8 15.5 18.9 17.4 13.4  6.0 -0.8 -0.9  7.8    6
1751 -1.5 -3.6  3.3  6.2 12.7 15.9 17.7 17.2 12.0 11.3  0.8-13.7  6.5    6
1752 -5.7 -3.5  1.0  4.5 10.1 15.5 19.7 18.0 11.7  7.3  3.8 -0.7  6.8    6
1753 -3.6 -1.8  3.4  6.8 11.7 16.7 18.4 17.1 13.6  9.1  2.2 -3.6  7.5    8
1754 -2.9 -3.5 -0.5  6.7 12.7 16.5 17.5 17.3 13.1  8.8  3.3 -0.3  7.4    8
1755 -5.5 -4.7  0.4  8.9 11.8 17.8 19.0 16.3 12.6  7.9  2.9 -0.1  7.3    9
1756  0.0  1.5  2.4  5.6 10.6 17.6 18.8 16.3 13.9  7.8  0.7 -2.4  7.7   10
1757 -3.8 -0.3  2.5  8.4 12.2 17.8 21.6 18.4 13.4  5.3  3.9 -1.7  8.1   12
1758 -4.3 -1.2  2.9  7.3 13.8 17.3 17.5 18.1 12.5  6.5  4.0  0.1  7.9   13
1759  0.8  2.2  3.9  8.2 12.4 17.7 20.4 18.8 14.8  9.9  2.1 -2.4  9.1   14
1760 -3.8 -0.5  1.6  8.1 12.8 17.0 19.1 17.5 15.1  8.6  4.0  1.2  8.4   14
1761 -1.9  0.9  5.2  7.4 13.7 18.1 19.1 18.9 15.1  6.7  3.4 -2.4  8.7   15
1762  1.2  0.2  0.9 10.1 13.5 17.0 19.0 16.5 13.5  6.2  3.5 -1.3  8.4   15
1763 -4.3  2.0  2.2  7.3 11.5 16.7 19.2 19.0 13.5  7.8  4.1  1.7  8.4   16
1764  2.1  3.7  3.5  7.7 13.8 16.2 19.7 17.1 13.2  8.4  3.7  0.8  9.2   17
1765  0.7 -1.6  5.3  8.7 12.2 16.6 17.5 18.3 14.0  9.6  4.3 -0.2  8.8   17
1766 -3.4 -0.5  4.1  9.8 13.2 17.6 19.0 18.5 15.0  9.2  5.4 -0.4  9.0   17
1767 -6.0  2.4  4.0  6.8 11.8 16.2 18.5 18.9 14.8  9.2  6.3 -1.2  8.5   18
1768 -3.4  0.1  2.1  7.8 13.0 16.6 19.2 18.3 13.3  8.3  4.5  1.2  8.4   19
1769  0.5  0.2  3.6  8.4 12.7 16.9 19.0 17.5 14.2  5.9  4.1  0.6  8.6   19
1770 -1.5  0.7  0.4  7.0 12.9 16.3 18.4 18.8 15.5  9.2  4.0  1.5  8.6   19
1771 -1.3 -1.7  1.1  5.3 14.5 17.3 18.7 17.7 14.4  9.7  3.0  1.8  8.4   20
1772 -1.3  0.1  3.3  7.5 11.0 17.6 19.0 18.3 14.9 11.0  6.4  2.0  9.2   20
1773  0.5 -0.8  3.5  8.5 13.9 16.4 18.6 18.8 15.2 10.6  4.6  2.2  9.3   20
1774 -2.5  0.8  4.6  9.4 13.0 17.6 18.9 18.7 13.8  8.5 -0.3 -2.7  8.3   21
1775 -1.9  1.6  3.8  6.9 12.0 17.9 19.7 19.3 15.5  9.4  2.7 -1.0  8.8   22
1776 -7.8  0.1  3.3  7.1 10.4 17.2 19.4 18.4 13.4  8.5  3.2 -0.8  7.7   22
1777 -3.4 -2.5  3.2  5.6 12.3 15.9 17.4 18.4 13.6  8.4  3.9 -1.9  7.6   24
1778 -2.9 -1.8  2.2  8.9 13.3 16.1 20.2 18.7 12.7  6.8  3.3  0.9  8.2   24
1779 -5.3  1.3  4.1  9.6 14.2 15.3 18.3 19.0 15.3 10.1  3.2  0.0  8.8   26
1780 -5.7 -3.5  4.8  6.1 13.9 16.5 19.0 18.5 13.8  9.7  2.8 -1.9  7.8   27
1781 -1.9  0.0  4.2  9.5 13.6 17.5 19.0 19.6 14.9  7.5  3.8 -0.9  8.9   31
1782 -1.2 -4.4  0.9  6.1 11.4 16.9 18.9 17.6 13.9  7.2  0.8 -1.2  7.2   31
1783 -1.1  1.7  1.9  8.6 13.9 17.4 19.8 18.4 14.8  9.6  3.3 -1.8  8.9   31
1784 -4.3 -2.5  1.3  5.9 14.4 16.8 18.5 17.6 15.4  6.6  4.1 -1.4  7.7   32
1785 -1.0 -2.6 -2.2  5.8 12.1 16.4 17.8 17.0 15.1  8.1  4.0 -0.8  7.5   32
1786 -1.6 -0.8  1.0  8.8 12.1 17.2 17.1 17.0 13.3  6.7  0.4 -0.6  7.6   32
1787 -1.7  1.1  4.7  6.9 11.9 17.5 18.0 18.3 14.4 10.4  3.9  1.7  8.9   32
1788 -0.7 -0.5  2.3  8.3 13.2 17.8 20.5 17.2 15.2  8.0  2.2 -8.3  7.9   32
1789 -3.9  0.2 -1.3  8.1 15.0 16.3 19.2 18.5 14.5  8.8  3.6  1.4  8.4   32
1790  0.0  2.3  4.2  6.0 14.2 17.2 17.2 18.0 13.4  9.3  3.6  1.0  8.9   32
1791  1.2  0.5  4.2  9.9 12.6 16.6 18.8 19.1 13.6  8.4  2.6  0.5  9.0   32
1792 -2.5 -1.5  3.3  9.1 12.3 16.8 19.3 18.1 13.5  8.3  3.6  0.0  8.4   34
1793 -2.7  1.5  3.1  6.9 12.4 16.0 20.1 18.8 13.5 10.3  4.3  1.0  8.8   34
1794 -0.6  2.2  5.7 10.8 13.4 17.3 20.4 17.2 12.8  8.6  4.1 -0.6  9.3   35
1795 -6.7 -1.7  2.1  9.7 12.5 16.7 17.1 18.2 14.9 11.1  2.7  1.9  8.2   37
1796  3.6  1.3  1.2  8.6 13.3 16.9 18.6 18.5 15.4  8.8  3.2 -2.9  8.9   38
1797 -1.1  1.1  2.5  8.8 14.2 16.4 20.1 19.1 15.6  9.6  4.5  1.9  9.4   38
1798  0.0  1.7  3.9  9.1 14.6 18.2 19.6 19.6 15.7  9.7  3.7 -2.3  9.5   38
1799 -3.2 -1.7  2.2  7.5 12.4 16.5 18.5 18.3 14.7  9.6  5.2 -2.4  8.1   39
1800 -0.3  0.0  1.5 12.3 15.2 15.8 18.7 19.1 15.2  9.9  5.9  1.7  9.6   39
1801  1.6  1.5  6.5  9.0 15.3 16.7 19.1 18.3 16.4 11.5  5.9  1.6 10.3   40
1802 -1.4  1.6  5.6 10.2 13.1 17.7 18.5 20.5 15.7 12.4  5.4  2.1 10.1   40
1803 -2.7 -0.7  4.3 11.3 12.7 17.0 20.4 19.7 13.6  9.7  5.0  1.4  9.3   40
1804  2.3 -0.4  2.0  8.3 15.0 17.5 19.0 18.4 16.2 10.2  3.6 -1.6  9.2   40
1805 -2.5 -0.3  3.4  7.2 12.1 15.6 18.2 17.6 15.4  6.6  2.0  1.0  8.0   40
1806  1.4  2.2  3.7  6.7 14.9 16.4 18.0 18.3 15.8  9.6  6.0  4.2  9.8   41
1807 -0.5  1.8  1.4  6.5 13.7 16.5 20.3 21.6 13.6 10.5  5.2  1.2  9.3   42
1808 -0.8 -1.2 -0.5  6.1 14.7 16.7 20.1 19.4 15.1  8.0  3.7 -2.9  8.2   43
1809 -3.3  1.6  2.3  5.1 13.9 16.5 18.3 18.4 14.2  8.7  2.7  2.0  8.4   43
1810 -2.1 -1.0  3.5  6.9 12.1 15.4 18.2 18.0 15.8  9.1  4.1  1.5  8.5   43
1811 -3.5  0.5  5.6  8.5 15.7 19.1 20.2 18.3 14.6 11.6  5.3  0.8  9.7   44
1812 -3.5  0.4  2.0  5.6 13.1 16.9 18.0 18.3 13.4 10.3  2.4 -4.2  7.7   48
1813 -3.2  2.0  3.4  9.7 14.1 16.5 18.6 17.9 14.8  8.9  4.4  0.5  9.0   49
1814 -3.8 -3.5  1.8  9.7 11.4 16.2 19.7 18.2 13.4  8.5  4.7  1.5  8.1   49
1815 -3.6  1.3  4.7  8.6 13.6 16.4 17.5 17.5 14.1 10.2  2.9 -1.9  8.4   49
1816 -1.2 -2.5  2.4  7.8 12.1 15.9 17.7 16.8 14.0  9.3  3.8  0.2  8.0   53
1817  1.5  2.4  3.8  6.5 13.3 17.6 18.7 18.2 15.1  7.0  4.9 -1.5  9.0   55
1818  0.3  0.4  4.7  8.7 13.3 18.2 20.0 17.8 14.9 10.0  5.5  0.4  9.5   55
1819  0.7  1.0  4.3  9.0 13.7 18.2 19.9 19.5 15.9  9.4  3.4 -1.6  9.5   56
1820 -4.3  0.6  3.2 10.2 14.5 17.0 19.5 19.6 14.5  9.2  2.8 -1.6  8.8   60
1821 -1.2 -0.5  3.1  9.7 13.6 15.9 18.2 18.6 15.7 10.1  5.4  1.6  9.2   63
1822 -0.6  1.9  6.6 10.2 15.3 19.3 20.4 19.1 15.3 10.9  5.9 -1.2 10.3   66
1823 -4.4 -1.1  3.8  8.2 14.2 17.7 19.4 19.6 15.4  9.8  3.5  0.8  8.9   68
1824 -0.5  0.1  3.1  7.9 12.7 16.9 19.7 18.8 16.0  9.5  4.8  2.0  9.2   70
1825 -0.2 -0.1  2.8  9.0 13.9 18.1 19.9 19.0 15.3  9.9  5.1  1.7  9.5   73
1826 -4.3 -0.2  3.7  8.1 14.7 18.7 21.5 20.5 15.6 10.3  3.8  1.2  9.5   74
1827 -2.7 -2.5  4.1 10.1 14.8 18.4 20.6 18.8 15.4 10.2  2.3  0.6  9.2   75
1828 -1.9 -0.4  3.9  8.4 14.4 19.5 20.7 19.4 15.0  9.6  4.7  1.0  9.5   77
1829 -3.9 -3.6  1.3  8.2 14.0 17.6 19.9 18.4 14.3  8.6  1.4 -2.9  7.8   83
1830 -5.5 -2.8  3.4  9.6 13.5 17.8 20.8 19.3 14.4  9.5  5.9  0.0  8.8   87
1831 -4.7 -1.8  3.3  9.3 13.8 18.6 20.6 19.3 14.5 10.8  3.2 -2.9  8.7   88
1832 -2.3 -1.0  2.8  7.9 12.9 17.6 19.3 19.2 14.4 10.1  3.3 -1.1  8.6   95
1833 -2.1  0.3  2.2  8.7 15.7 18.5 19.8 17.7 15.0  9.4  4.2  1.1  9.2   96
1834 -1.6  0.9  4.0  8.5 14.9 18.4 21.7 20.4 16.2  9.7  4.0 -0.1  9.8   99
1835 -0.6 -0.3  3.1  8.0 13.6 18.0 20.2 18.5 14.6  9.7  2.1 -3.3  8.6  101
1836 -2.3 -1.7  4.0  8.0 12.4 17.3 19.5 17.9 14.4  9.1  2.8 -0.3  8.4  109
1837 -2.8 -0.8  1.0  6.7 12.5 17.7 19.2 19.5 14.7  9.6  4.7 -0.2  8.5  114
1838 -4.1 -4.3  3.1  6.9 13.2 18.1 20.4 18.8 15.7  8.9  3.0 -1.1  8.2  117
1839 -2.3 -0.9  0.8  7.3 13.8 17.8 20.8 18.9 15.2 10.3  3.1 -1.9  8.6  120
1840 -2.6  0.0  1.8  9.5 14.0 18.2 20.0 19.7 15.2  9.1  4.5 -2.7  8.9  123
1841 -1.7 -2.1  3.7  8.5 15.1 18.5 19.8 19.6 16.2 10.0  4.3  1.3  9.4  129
1842 -2.2  0.2  4.7  8.7 13.9 17.9 19.9 19.9 15.1  9.0  3.0  0.6  9.2  131
1843  1.0  0.0  1.7  8.7 13.3 17.6 19.8 19.9 16.2  9.7  4.2  1.7  9.5  133
1844 -2.5 -1.1  3.2 10.4 14.8 18.4 19.8 18.9 15.9 10.1  4.3 -1.2  9.2  134
1845  0.1 -2.3  2.0  9.3 13.1 18.7 20.7 19.3 15.4  9.9  5.3 -0.7  9.2  138
1846 -0.3 -0.1  5.0  9.7 14.7 18.9 21.3 21.2 17.2 10.6  4.7 -0.7 10.2  141
1847 -2.0 -0.6  2.1  8.0 14.7 17.7 21.0 20.2 15.6  9.7  5.4  0.0  9.3  143
1848 -4.0  0.4  3.5  9.6 14.7 18.7 20.1 19.3 14.8 10.4  3.5  0.7  9.3  148
1849 -2.2  0.0  3.7  7.9 13.9 18.6 20.3 19.4 15.6 10.7  6.1 -0.5  9.5  152
1850 -2.8  1.5  2.8  8.3 13.3 18.8 20.9 20.1 15.5  9.9  5.6  0.8  9.6  154
1851  0.2  1.0  4.1  9.3 13.7 18.2 20.0 19.5 15.8 11.5  4.0  0.3  9.8  164
1852 -0.6  0.8  3.3  7.6 14.8 18.5 21.1 19.7 16.0 10.9  5.7  3.6 10.1  169
1853  1.2  0.2  3.1  8.8 14.4 18.9 20.9 20.0 16.1 11.1  5.6  0.3 10.1  174
1854 -0.4  0.8  5.1  9.6 15.4 18.6 21.8 20.5 16.9 12.2  5.1  2.0 10.6  183
1855 -0.4 -1.5  3.9 10.2 14.9 18.7 21.3 20.4 16.7 11.9  5.9 -0.2 10.2  189
1856 -0.5  0.7  3.0 10.4 14.0 19.6 20.8 19.8 16.0 11.3  4.2  1.0 10.0  197
1857 -2.2  2.1  4.1  8.4 13.9 18.2 20.9 20.3 16.7 11.7  5.5  3.5 10.3  203
1858  1.0 -0.7  4.6 10.0 14.4 19.9 20.9 20.0 16.9 12.2  3.9  2.2 10.4  206
1859  1.0  2.8  6.4  9.5 15.3 18.6 21.4 20.5 16.0 11.0  6.1  0.0 10.7  211
1860  1.3  0.4  4.1  9.3 14.8 18.7 20.0 19.8 16.2 11.3  5.2  0.6 10.1  214
1861 -1.5  3.0  5.6  8.9 13.0 18.6 20.1 19.9 15.8 11.5  5.7  2.1 10.2  217
1862 -1.1 -0.4  4.2  9.1 14.3 17.3 19.6 18.9 15.8 10.8  4.1  0.6  9.4  222
1863  1.5  1.3  3.7  9.0 14.2 17.4 19.4 19.5 15.0 10.2  5.4  1.0  9.8  223
1864 -1.8  0.9  4.3  8.3 13.5 17.9 19.9 18.7 15.2  9.1  4.2 -0.2  9.2  234
1865  0.1  0.1  3.7 10.3 15.0 18.1 20.2 18.9 17.3 10.7  6.7  1.9 10.2  239
1866  1.7  2.0  4.3 10.4 13.0 18.2 20.0 18.1 16.1 10.8  6.1  2.1 10.2  259
1867 -0.6  3.2  2.8  9.4 12.7 18.1 19.4 19.6 16.3 11.2  5.9  1.0  9.9  263
1868 -0.6  1.3  5.8  9.1 15.1 18.6 21.5 19.9 15.9 10.8  5.3  2.3 10.4  269
1869  2.1  4.1  4.2 10.4 14.5 17.6 20.3 19.6 16.6 10.1  5.7  2.3 10.6  277
1870  2.3  1.4  4.3 10.7 15.6 19.3 21.5 19.7 16.7 11.8  7.2  1.0 11.0  289
1871  0.8  2.2  7.5 11.1 14.8 18.7 20.9 20.8 16.2 11.9  5.3  1.0 10.9  304
1872  1.3  2.5  4.8 10.9 15.5 19.2 21.4 20.6 17.1 11.9  6.0  1.3 11.0  320
1873  1.3  1.7  5.7  9.6 14.4 19.4 21.3 20.5 16.5 11.5  5.9  3.2 10.9  336
1874  2.8  2.6  5.7  9.6 14.9 19.4 21.3 20.1 17.6 12.5  6.6  3.0 11.3  345
1875  0.1  0.5  4.6  9.8 15.6 19.1 20.8 20.2 16.6 11.7  6.3  3.8 10.8  358
1876  3.5  4.3  6.2 11.4 15.1 19.8 21.7 20.8 17.1 12.5  7.2  2.2 11.8  374
1877  2.6  5.4  6.6 11.1 14.9 19.6 21.3 20.9 17.5 12.9  8.7  6.0 12.3  385
1878  3.7  5.9  9.5 13.4 16.2 19.7 21.9 21.4 18.3 13.9  8.8  3.4 13.0  400
1879  2.3  4.2  8.2 11.7 16.2 19.5 21.4 20.9 17.6 14.4  8.0  3.5 12.3  408
1880  5.0  5.0  7.5 12.3 17.0 19.7 21.4 20.9 17.9 12.7  6.6  3.7 12.5  414
1881  0.7  3.2  6.6 11.3 17.0 19.2 21.9 21.3 18.5 12.9  8.0  5.5 12.2  445
1882  3.7  5.3  8.2 11.9 15.6 19.6 21.4 21.2 18.1 13.8  7.4  3.2 12.4  459
1883  0.6  2.7  5.4 11.6 15.8 20.3 21.7 20.8 17.6 13.0  7.9  3.8 11.8  477
1884  1.3  3.5  6.5 10.9 16.1 19.5 21.4 20.9 18.5 13.7  7.1  2.9 11.9  488
1885  0.4  1.8  5.6 11.3 15.6 19.6 22.0 20.6 17.6 12.3  7.6  3.7 11.5  501
1886  0.2  2.2  5.7 12.3 16.6 19.6 21.8 21.3 18.3 13.3  6.9  2.5 11.7  521
1887  0.7  2.7  6.2 11.1 17.1 20.1 22.6 20.8 17.8 12.0  7.2  2.6 11.7  538
1888 -0.4  2.3  4.7 12.1 15.8 20.0 21.8 21.0 17.6 12.3  7.3  3.7 11.5  550
1889  1.7  1.7  7.0 12.1 16.6 19.9 21.9 21.0 17.3 12.2  6.9  5.1 11.9  564
1890  2.4  3.5  5.9 11.9 16.0 20.4 22.1 20.9 17.7 12.5  7.8  2.6 12.0  576
1891  0.9  1.7  4.8 11.3 15.6 19.7 21.1 21.0 18.5 12.3  6.0  3.9 11.4  620
1892 -0.1  3.1  5.1 10.8 15.3 20.1 21.8 21.4 18.2 12.8  6.3  0.9 11.3  639
1893 -2.0  0.6  5.3 10.8 15.4 20.2 22.3 21.2 17.7 12.6  6.2  2.6 11.1  657
1894  0.7  1.0  7.2 11.8 16.3 20.1 22.4 21.6 18.0 12.8  6.4  2.8 11.8  664
1895 -0.8 -0.8  5.5 12.0 16.3 20.1 21.5 21.4 18.7 11.5  6.3  2.2 11.2  675
1896  0.9  2.7  4.8 11.9 17.2 20.5 22.4 21.6 17.3 12.1  5.7  3.0 11.7  681
1897 -0.1  2.3  5.5 11.4 16.3 20.0 22.5 21.2 18.9 13.4  6.2  1.3 11.6  694
1898  1.7  2.5  6.1 10.9 16.0 20.3 22.2 21.9 18.5 11.9  5.7  1.3 11.6  710
1899  0.8 -0.8  4.5 11.3 16.0 20.1 22.1 21.6 17.9 13.2  8.3  1.6 11.4  718
1900  1.6  0.6  5.3 11.5 16.5 20.4 22.2 22.3 18.4 14.2  6.8  3.0 11.9  726
1901  1.1  0.5  6.2 11.0 16.2 20.3 23.5 21.9 17.6 13.3  6.4  1.5 11.6  747
1902  1.0  1.3  6.9 11.1 16.6 19.6 21.7 21.0 17.2 12.9  7.6  1.2 11.5  753
1903  1.1  1.5  7.3 11.1 16.0 18.8 21.5 20.8 17.3 12.7  6.1  1.1 11.3  764
1904 -0.5  1.0  6.1 10.4 16.0 19.4 21.3 20.8 17.9 12.7  7.3  1.9 11.2  771
1905 -0.5 -0.3  7.7 11.1 15.8 19.9 21.7 21.5 18.5 12.0  7.3  2.4 11.4  790
1906  2.3  2.2  4.5 12.3 16.1 19.7 21.8 21.6 18.6 12.4  6.6  3.0 11.8  797
1907  1.0  2.3  7.8  9.6 14.2 18.7 21.8 20.9 17.8 12.7  6.5  3.0 11.4  812
1908  1.6  2.1  7.0 11.8 15.7 19.4 22.0 20.9 18.4 12.2  7.0  2.5 11.7  819
1909  1.2  2.7  5.7 10.4 15.0 19.9 21.6 21.7 17.8 12.3  8.2 -0.1 11.4  831
1910  0.8  0.9  9.3 12.3 15.4 19.6 22.2 20.9 18.0 13.3  6.2  1.6 11.7  842
1911  1.4  2.1  6.9 10.8 16.5 20.5 21.9 21.0 18.3 12.2  5.3  2.5 11.6  849
1912 -1.5  1.3  4.3 11.1 16.0 19.2 21.5 20.4 16.9 12.1  6.9  2.6 10.9  864
1913  1.2  0.7  5.6 11.6 15.6 19.6 21.8 21.8 17.4 11.9  8.2  3.0 11.5  872
1914  2.5  1.0  6.2 11.3 16.3 20.1 22.2 21.2 17.6 13.2  7.2  0.1 11.6  885
1915  0.1  3.3  4.6 12.7 14.9 18.7 21.1 20.5 17.7 13.0  7.0  2.0 11.3  894
1916  0.1  1.8  5.9 10.8 15.3 18.5 22.2 21.2 17.2 11.9  6.1  0.3 10.9  902
1917 -0.1  0.2  4.7 10.0 13.5 18.9 22.2 20.8 17.5 11.0  7.2  0.3 10.5  910
1918 -1.7  2.2  7.7 10.3 15.8 20.2 21.4 21.4 16.7 13.6  6.4  2.9 11.4  917
1919  1.4  1.8  6.0 11.2 15.4 20.0 22.2 21.2 18.2 12.1  5.6  0.4 11.3  918
1920  0.4  2.3  6.2  9.6 15.3 19.2 21.6 20.8 17.9 12.8  6.0  2.3 11.2  921
1921  2.7  3.7  8.6 11.6 15.9 20.5 22.5 21.2 18.4 13.2  6.8  3.1 12.4  946
1922 -0.4  1.8  6.1 11.0 16.2 20.3 21.6 21.4 18.6 13.0  6.9  2.4 11.6  956
1923  2.5  0.8  5.3 10.7 15.4 19.5 21.9 20.9 18.0 12.0  7.5  3.8 11.5  967
1924 -0.4  2.8  5.0 10.9 15.0 19.6 21.3 21.2 17.1 13.2  7.1  0.4 11.1  978
1925  0.6  4.3  7.3 12.5 15.6 20.1 22.0 21.1 18.5 10.7  6.4  2.3 11.8  987
1926  1.2  4.0  6.0 10.9 16.0 19.4 21.9 21.4 17.5 12.9  6.6  1.6 11.6 1009
1927  1.1  3.8  6.7 11.2 15.4 19.1 21.8 20.3 17.9 13.4  7.6  0.4 11.6 1017
1928  1.5  2.6  6.6 10.1 16.1 18.6 22.0 21.2 17.2 13.0  6.9  2.4 11.5 1023
1929 -0.9 -0.6  7.0 11.0 15.3 19.2 21.9 21.4 17.4 12.7  5.9  2.4 11.1 1042
1930 -1.4  4.3  6.1 12.2 15.5 19.7 22.5 21.7 18.2 11.9  6.7  1.7 11.6 1048
1931  2.2  3.8  5.9 11.3 15.5 20.2 22.6 21.1 18.8 13.7  7.7  3.6 12.2 1120
1932  2.3  3.4  4.9 11.5 15.8 19.7 21.8 21.3 17.8 12.4  6.6  1.7 11.6 1137
1933  2.5  1.2  6.3 10.9 15.5 20.4 22.2 21.0 18.5 13.0  7.0  3.2 11.8 1152
1934  2.8  2.9  6.8 12.1 17.4 20.3 22.7 21.5 17.4 13.5  8.4  2.8 12.4 1162
1935  1.2  3.9  7.3 10.6 14.6 19.1 22.2 21.3 17.6 12.7  6.1  1.7 11.5 1177
1936  0.0 -0.7  6.8 10.7 16.7 20.1 22.8 21.8 18.1 12.5  6.2  3.1 11.5 1203
1937 -0.6  1.8  5.1 10.7 16.1 19.6 22.0 21.9 17.9 12.6  6.5  2.0 11.3 1221
1938  1.5  3.2  7.7 11.6 15.5 19.4 21.8 21.6 18.3 13.5  6.5  2.4 11.9 1248
1939  2.0  1.4  6.3 11.1 16.4 19.5 22.0 21.2 18.2 12.5  6.8  4.1 11.8 1263
1940 -1.9  2.0  5.9 10.7 15.6 19.7 21.8 20.9 17.7 13.0  5.8  3.2 11.2 1282
1941  1.6  2.7  5.8 11.8 16.3 19.4 21.9 20.9 17.5 13.3  7.4  3.7 11.9 1363
1942  1.0  1.5  6.5 11.9 15.4 19.2 21.6 20.8 17.4 13.0  7.3  2.5 11.5 1380
1943  0.5  3.6  5.6 11.8 15.6 19.5 21.8 21.2 17.5 12.8  6.7  2.8 11.6 1393
1944  2.2  3.1  5.7 10.6 16.3 19.3 21.3 20.9 17.9 13.1  6.8  1.6 11.6 1408
1945  0.8  2.8  7.8 11.2 14.8 18.4 21.1 21.0 17.6 12.7  6.8  1.0 11.3 1415
1946  1.7  3.2  8.3 12.4 15.2 19.2 21.5 20.5 17.5 12.4  7.0  3.1 11.8 1432
1947  1.4  1.8  6.0 11.4 15.6 18.8 21.2 21.5 18.1 14.3  6.2  2.7 11.6 1453
1948  0.9  2.1  5.8 12.0 15.8 19.6 21.3 20.7 17.9 12.5  7.2  2.5 11.5 1473
1949  0.6  2.3  6.4 11.7 16.2 19.6 21.6 20.9 17.2 12.9  8.1  2.8 11.7 1489
1950  0.9  3.0  5.8 10.6 15.5 19.2 20.7 20.2 17.2 13.6  6.4  2.6 11.3 1493
1951  3.5  4.8  7.5 12.5 16.7 19.3 21.6 21.1 18.2 13.9  8.1  4.9 12.7 2009
1952  4.5  5.8  7.6 13.1 16.7 20.3 21.9 21.3 18.6 13.7  8.5  5.4 13.1 2053
1953  5.4  6.1  9.4 12.6 16.7 20.3 21.8 21.3 18.7 14.8  9.5  5.8 13.5 2074
1954  3.6  6.7  8.2 13.3 16.2 19.9 21.8 21.0 18.7 14.4 10.0  5.7 13.3 2100
1955  4.4  5.0  8.1 13.2 16.9 19.4 21.8 21.6 18.6 14.4  8.2  4.8 13.0 2121
1956  4.2  4.4  8.3 12.3 16.8 20.0 21.2 20.7 18.0 14.5  8.6  6.0 12.9 2139
1957  3.3  6.5  8.8 12.9 16.5 19.9 21.5 20.8 18.1 13.6  9.1  6.6 13.1 2159
1958  4.8  5.4  7.9 12.7 17.2 19.4 21.2 21.1 18.2 14.2  9.5  5.2 13.1 2168
1959  3.9  5.2  8.9 13.0 16.6 19.9 21.5 21.1 18.0 13.6  8.2  6.0 13.0 2176
1960  4.0  5.1  7.0 13.0 16.3 19.8 21.3 20.8 18.4 14.2  9.4  5.0 12.9 2179
1961  4.0  6.5  9.4 12.4 16.3 19.9 21.2 21.0 17.9 14.0  9.0  4.7 13.0 2445
1962  3.7  5.9  7.9 13.0 16.9 19.4 20.8 20.8 17.8 14.5  9.5  5.4 13.0 2457
1963  2.6  5.4  9.0 12.9 16.6 19.6 21.3 20.7 18.4 15.3  9.9  4.2 13.0 2476
1964  4.5  5.0  8.0 12.8 16.8 19.5 21.4 20.2 17.7 13.7  9.2  4.9 12.8 2488
1965  4.4  4.9  7.5 12.6 16.6 19.3 20.9 20.4 17.4 14.1  9.4  6.0 12.8 2488
1966  3.1  5.2  9.1 12.5 16.5 19.6 21.6 20.6 18.0 13.9  9.4  5.2 12.9 2502
1967  4.7  5.1  9.2 12.8 16.1 19.3 21.1 20.7 18.0 14.3  9.1  5.2 13.0 2511
1968  3.4  5.1  9.7 12.9 16.1 19.6 21.1 20.4 17.9 14.1  9.1  4.6 12.8 2518
1969  3.4  4.9  7.6 13.2 17.0 19.3 21.4 21.0 18.2 13.6  9.4  5.7 12.9 2529
1970  3.6  6.2  8.2 12.9 16.9 19.9 21.4 21.0 18.0 13.7  9.2  5.4 13.0 2525
1971  3.5  4.8  7.7 12.2 15.9 19.5 20.9 20.7 18.0 14.1  8.8  5.3 12.6 2444
1972  3.2  4.6  8.8 12.3 16.3 19.3 20.8 20.6 17.5 13.0  7.9  4.1 12.4 2434
1973  3.6  5.3  9.2 12.2 16.2 19.8 21.2 20.8 17.8 13.9  8.3  4.7 12.8 2437
1974  3.5  5.0  9.0 12.7 16.1 19.3 21.2 20.3 17.1 13.1  8.5  4.7 12.5 2445
1975  4.1  4.6  7.5 11.5 16.5 19.2 21.1 20.4 17.3 13.4  8.4  4.5 12.4 2450
1976  3.3  6.1  8.2 12.7 15.8 19.2 20.8 20.1 17.4 12.0  7.3  3.4 12.2 2445
1977  1.5  5.5  9.2 13.4 16.8 19.8 21.3 20.5 17.9 13.3  9.0  4.4 12.7 2444
1978  2.7  3.7  8.4 12.5 16.1 19.4 21.1 20.3 18.0 13.7  8.8  4.4 12.4 2439
1979  1.6  3.2  8.7 12.0 16.1 19.3 21.0 20.5 18.1 14.1  8.5  6.0 12.4 2430
1980  3.6  4.7  7.7 12.7 16.4 19.4 21.6 20.8 18.1 13.2  8.7  4.9 12.6 2420
1981  1.4  3.3  7.3 11.8 15.0 18.9 20.7 20.1 16.9 11.8  6.8  2.6 11.4 3778
1982 -0.5  1.7  6.2 10.9 15.8 18.5 20.7 20.1 17.2 12.5  7.3  4.1 11.2 3765
1983  2.9  3.4  7.1 10.9 15.2 18.6 21.3 20.9 17.5 12.9  7.8  2.1 11.7 3754
1984  1.4  3.2  5.9 10.7 15.3 18.7 20.5 20.3 16.6 12.8  7.0  2.6 11.2 3708
1985 -0.2  1.2  6.4 11.6 15.7 18.3 20.6 20.1 16.7 12.5  6.3  1.8 10.9 3680
1986  2.1  2.1  7.2 11.5 15.9 19.2 20.6 19.9 16.6 12.2  6.9  2.9 11.4 3664
1987  0.9  3.8  6.0 11.5 15.7 19.0 21.0 20.1 17.4 12.3  7.1  3.6 11.5 3598
1988  3.0  3.1  6.8 11.4 15.7 18.8 20.7 20.0 17.0 12.6  7.0  4.3 11.7 3538
1989  3.2  4.2  7.7 11.2 15.4 18.2 20.3 19.6 16.6 12.4  6.8  3.4 11.6 3327
1990  2.0  4.4  8.3 11.2 15.3 18.5 20.5 20.4 16.8 13.2-99.0-99.0 13.1 3225
AA    2.0  3.4  7.1 11.7 15.9 19.4 21.4 20.8 17.7 13.1  7.6  3.4 12.0
Ad   -0.0  1.4  4.7  9.6 14.3 18.0 19.9 19.2 15.9 10.8  5.4  1.6 10.1
 
For Country Code ALL
 
From input file ./data/v1.mean

v2

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
--------------------------------------------------------------------------
1701 -4.2 -1.5  1.6-99.0-99.0 15.4 18.9 15.8-99.0-99.0-99.0 -0.5  6.5    1
1702  2.0 -0.5  0.6  2.6 10.9 16.0 16.0 15.8 10.1  7.5  0.2  0.6  6.8    1
1703 -2.8 -0.9  0.6  7.7 14.1 16.1 15.4 16.3 11.4  6.1  2.2  2.5  7.4    1
1704 -4.9 -0.5  3.9  9.4 11.8 14.1 17.1-99.0-99.0-99.0-99.0 -0.9  6.2    1
1705 -7.1-99.0  1.0-99.0-99.0 16.0 18.3 17.8  8.7  7.5  0.7  1.8  7.2    1
1706 -1.2 -1.0  2.8  7.4 12.8 17.2 16.6 15.6 11.8  8.5  3.5  2.5  8.0    2
1707 -0.5  0.8  2.4  6.4 11.7 17.2 18.0 15.6 12.6  6.0  3.8  1.7  8.0    2
1708  3.0  0.9  4.7  7.7 11.1 14.3 15.3 17.9 14.3  7.9  3.3 -1.6  8.2    2
1709 -9.0 -0.9  0.9  9.4 11.7 16.7 16.0 16.0 12.2  8.1  5.6  2.0  7.4    2
1710 -1.1 -0.2  4.1  6.9 12.9 15.2 15.2 16.5 13.8  9.4  7.4  6.5  8.9    2
1711  3.5  0.0  4.7  9.5 12.2 16.9 16.0 15.6 13.3  9.3  6.5  1.5  9.1    1
1712  0.2  2.9  4.1  7.7 12.3 16.3 16.8 14.9 13.1  9.5  5.0  4.2  8.9    1
1713 -0.3  5.0  1.0  5.3 10.5 13.6 14.8 15.4 13.9  9.3  3.4  2.5  7.9    1
1714  1.9  3.8  5.0  7.9 10.2 14.5 18.5 13.8 13.0  9.7  4.6  2.4  8.8    1
1715  0.7  3.5  5.7  9.6 11.6 14.5 15.8 17.0 14.1 10.3  6.3 -1.5  9.0    1
1716 -5.0  1.5  3.3  9.1 11.3 14.0 16.3 15.5 12.4  8.3  3.9  1.2  7.7    1
1717  0.9  0.7  3.4  7.2 10.2 15.3 15.7 15.5 13.9  9.3  3.4  3.5  8.3    1
1718 -1.6 -0.8  4.6  8.3 12.7 16.0 18.0 19.0 15.1  8.9  5.2  3.3  9.1    1
1719  0.5  2.5  3.5  5.6 13.4 16.0 20.1 18.9 14.1  8.2  5.0  1.3  9.1    1
1720  2.9  2.9  3.1  6.8 12.3 12.6 17.2 14.5 14.3  8.1  5.6  3.6  8.7    1
1721  3.5  0.1  0.8  8.9 10.2 15.3 15.2 16.5 14.4  8.6  5.8  1.9  8.4    1
1722  0.9  3.9  5.5  8.6 11.5 15.1 15.8 15.5 14.6 10.4  6.8  3.3  9.3    1
1723  0.3  2.5  6.4  8.4 12.4 15.6 15.6 15.9 13.9 11.0  2.2  4.7  9.1    1
1724  4.8  3.6  3.7  6.7 11.8 16.7 15.1 16.9 14.2  8.3  5.1  2.0  9.1    1
1725  2.3  0.4  3.5  7.0 10.6 14.0 14.6 14.3 12.5  8.0  3.0  2.0  7.7    1
1726 -1.8  0.2  2.5  7.8 14.1 16.2 15.6 14.4 14.2  9.2  5.3  0.1  8.1    1
1727  2.6  3.6  3.7  7.0 15.0 15.4 16.8 17.5 14.7 11.5  3.6  2.5  9.5    1
1728  2.5 -0.6  6.9  8.9 14.8 16.6 16.5 14.6 13.1  9.2  4.3 -0.6  8.8    2
1729 -3.1  0.3  0.2  6.3 11.1 16.2 17.8 17.7 16.9 12.1  5.3  5.3  8.8    2
1730  2.4  2.3  4.3  9.1 12.6 15.6 17.2 16.8 14.4  7.0  7.5  2.2  9.3    2
1731 -0.5 -0.4  3.3  6.4 12.0 15.3 16.4 16.8 14.8 11.9  6.5  3.2  8.8    2
1732 -0.5  3.3  5.3  9.7 12.9 14.2 16.1 16.2 14.1 10.4  4.4 -0.9  8.8    2
1733  4.3  4.5  5.1 10.5 11.5 15.3 18.3 16.5 12.0  8.2  5.5  5.6  9.8    2
1734  1.6  4.4  6.4  9.5 12.3 14.7 17.0 16.3 14.1  9.5  1.9  1.3  9.1    2
1735  3.0  2.4  5.8  9.6 12.2 15.5 16.1 16.5 15.2  7.5  4.0  3.0  9.2    2
1736  1.3  0.8  3.2  9.2 12.2 15.0 17.3 17.7 13.9  9.3  5.6  4.2  9.1    2
1737  4.0  3.0  5.4  7.3 13.7 16.0 16.6 14.5 14.5  8.7  4.3  2.1  9.2    2
1738  0.0  2.5  5.0  9.6 12.8 15.2 16.5 16.0 13.5  9.9  2.0  4.2  8.9    2
1739 -1.4  0.9  3.6  5.2 12.2 14.8 17.7 14.9 13.8  5.8 -0.9  1.9  7.4    3
1740 -6.3 -5.4  0.5  4.8  7.8 13.2 15.9 15.5 13.8  4.3  1.4  0.5  5.5    3
1741 -2.5  2.3  2.5  5.4  9.4 13.8 17.1 15.7 12.9  9.6  5.8  1.3  7.8    3
1742 -2.8  2.2  1.5  4.9  9.7 14.9 15.9 14.5 10.8  8.0  3.6 -2.5  6.7    3
1743  1.1  1.8  2.6  4.9 12.3 17.7 17.8 16.9 14.3  4.4  4.5 -0.1  8.2    5
1744 -3.7 -3.1  0.2  6.9 11.8 15.9 18.1 14.7 13.4  7.9  3.7 -1.3  7.0    5
1745 -3.1 -3.6 -0.1  6.6 12.7 17.0 18.0 16.8 16.0  8.5  4.7 -0.3  7.8    5
1746 -0.4 -0.4 -0.8  6.5 13.0 15.6 17.8 15.2 13.1  6.3  1.4  3.0  7.5    4
1747 -1.5 -0.2 -0.5  7.2 11.1 18.4 18.2 15.8 15.1  9.5  4.3  1.0  8.2    4
1748 -1.5 -1.5 -2.3  6.6 13.3 17.3 17.6 18.2 14.1  8.6  4.6  3.5  8.2    4
1749 -0.1 -1.3  0.4  6.6 13.3 15.2 17.1 17.5 13.7  7.8  3.6  0.9  7.9    4
1750 -0.5  1.4  4.4  7.3 12.0 16.2 19.1 17.5 13.6  6.2  3.1 -0.9  8.3    5
1751 -1.4 -3.5  3.5  6.4 12.7 16.0 18.0 17.4 11.9  7.4  2.0 -0.7  7.5    5
1752 -5.7 -3.6  1.0  4.4  9.7 15.3 19.4 17.6 11.4  7.2  3.7 -0.9  6.6    5
1753 -3.3 -1.7  3.5  6.9 11.7 16.5 18.4 16.9 13.9  9.4  2.4 -3.6  7.6    8
1754 -2.6 -3.3 -0.5  6.5 12.6 16.6 17.2 17.0 13.0  9.2  3.5 -0.1  7.4    8
1755 -5.3 -4.7  0.4  8.8 11.8 18.2 18.9 16.1 12.6  8.3  3.1  0.0  7.3   10
1756  0.1  1.6  2.4  5.4 10.4 17.2 19.0 16.1 13.9  8.1  0.9 -2.2  7.7   11
1757 -3.7 -0.2  2.4  8.4 12.1 17.9 21.8 18.5 13.4  5.4  4.2 -1.6  8.2   13
1758 -4.2 -1.2  2.7  7.0 13.4 17.5 17.4 18.1 12.5  7.6  4.1  0.1  7.9   13
1759  1.0  2.2  3.8  8.1 12.2 17.7 20.4 18.9 14.7 10.0  2.1 -2.4  9.1   14
1760 -3.8 -0.5  1.6  8.0 12.7 17.5 19.0 17.5 15.4  8.7  4.0  1.3  8.4   14
1761 -1.7  1.0  5.2  7.4 13.7 18.1 19.0 19.0 15.3  6.7  3.6 -2.3  8.7   14
1762  1.2  0.2  0.7 10.0 13.3 17.1 18.9 16.2 13.5  6.2  3.6 -1.2  8.3   13
1763 -4.0  2.3  2.3  7.2 11.3 16.5 19.0 18.7 13.4  7.9  4.3  2.2  8.4   15
1764  2.2  3.8  3.5  7.5 13.6 15.9 19.6 16.9 13.1  8.5  3.8  0.8  9.1   16
1765  1.0 -1.4  5.2  8.6 12.0 16.4 17.3 17.8 13.9  9.7  4.4 -0.1  8.7   16
1766 -3.0 -0.4  4.1  9.6 12.9 17.4 18.7 18.3 15.0  9.4  5.7 -0.2  9.0   16
1767 -5.5  2.5  4.0  6.5 11.6 15.6 18.1 18.7 14.9  9.3  6.5 -0.8  8.4   17
1768 -3.2  0.3  2.0  7.7 12.7 16.5 19.0 18.2 12.8  7.9  3.6  0.2  8.1   20
1769 -0.7 -0.9  2.4  7.5 12.0 16.2 18.5 17.0 14.2  6.1  4.1  1.0  8.1   21
1770 -1.2  0.9  0.4  6.8 12.8 16.2 18.3 18.7 15.7  9.3  4.1  1.8  8.7   21
1771 -1.4 -1.6  0.8  5.1 14.5 17.2 18.6 17.4 14.4  9.9  3.2  2.1  8.3   22
1772 -1.0  0.4  3.3  7.4 10.9 17.7 18.6 18.3 15.0 11.2  6.6  2.3  9.2   21
1773  0.9 -0.5  3.6  8.7 14.1 16.6 18.6 18.8 15.3 10.9  4.6  2.4  9.5   23
1774 -2.1  1.4  5.1  9.5 13.1 17.8 18.8 18.7 13.8  8.7 -0.1 -2.3  8.5   21
1775 -1.4  2.3  4.2  7.2 12.1 18.2 19.7 19.3 15.6  9.5  3.0 -0.4  9.1   23
1776 -8.0  0.2  3.0  6.9 10.2 17.2 19.4 18.2 13.2  8.3  3.0 -0.8  7.6   24
1777 -3.5 -2.7  3.0  5.4 12.3 15.9 17.3 18.2 13.3  8.3  4.0 -1.9  7.5   25
1778 -2.9 -1.7  2.1  8.8 13.3 16.3 20.3 18.6 12.5  6.6  3.1  0.9  8.2   24
1779 -5.0  1.5  4.3  9.5 14.1 15.5 18.4 19.1 15.4 10.3  3.3  0.2  8.9   27
1780 -5.4 -3.1  5.1  6.0 13.7 16.6 19.1 18.7 13.9  9.8  2.8 -1.7  8.0   28
1781 -2.0  0.0  4.2  9.5 14.1 17.7 19.1 19.7 15.2  7.6  3.9 -0.8  9.0   32
1782 -0.9 -4.2  1.2  6.4 11.7 17.3 19.3 18.0 14.1  7.2  0.8 -0.5  7.5   33
1783 -0.8  2.0  1.8  9.0 13.7 17.5 20.1 18.3 14.7  9.6  3.1 -2.0  8.9   32
1784 -4.7 -2.6  1.2  5.9 14.5 16.9 18.5 17.5 15.2  6.6  4.2 -1.5  7.6   33
1785 -1.0 -2.5 -2.3  5.7 12.1 16.3 17.9 17.0 15.2  8.2  4.0 -0.7  7.5   34
1786 -1.4 -0.6  1.0  9.0 12.2 17.3 17.2 17.1 13.3  6.8  0.6 -0.5  7.7   34
1787 -1.6  1.4  4.6  7.0 11.8 17.6 18.1 18.0 14.2 10.6  3.8  1.3  8.9   31
1788  0.0  0.3  3.0  8.9 14.0 18.1 20.8 17.5 15.7  8.6  2.4 -7.6  8.5   33
1789 -3.2  1.2 -0.4  8.7 15.7 16.4 19.4 18.7 14.8  9.3  3.8  1.8  8.9   32
1790  0.5  3.0  4.9  6.5 14.7 17.6 17.5 18.4 13.8  9.9  4.0  1.4  9.4   30
1791  1.9  1.3  4.8 10.6 13.1 17.1 19.3 19.7 14.3  9.2  3.5  1.4  9.7   33
1792 -1.3 -0.4  4.3  9.9 12.8 17.2 19.6 18.6 13.9  9.2  4.3  0.9  9.1   34
1793 -1.7  2.4  4.0  7.4 12.8 16.4 20.6 19.2 14.3 10.9  4.9  1.9  9.4   33
1794  0.1  3.3  6.5 11.5 13.9 17.8 21.1 17.7 13.5  9.4  5.0 -0.1 10.0   34
1795 -6.1 -0.7  3.0 10.3 13.1 17.2 17.4 18.7 15.6 11.7  3.4  2.9  8.9   36
1796  4.4  2.1  2.0  8.8 13.6 16.9 18.9 19.0 16.1  9.4  3.8 -2.1  9.4   38
1797 -0.2  1.7  3.1  9.4 14.6 16.5 20.4 19.4 16.0 10.0  5.0  2.6  9.9   36
1798  0.7  2.4  4.4  9.7 15.0 18.5 19.9 19.9 16.1 10.2  4.3 -1.8  9.9   39
1799 -3.0 -0.8  2.8  7.7 12.7 16.7 18.7 18.6 15.1 10.1  5.0 -1.8  8.5   40
1800  0.2  0.1  1.7 12.7 15.6 16.0 19.1 19.6 15.7 10.3  6.3  2.2 10.0   40
1801  1.9  1.8  6.8  9.6 15.8 17.0 19.6 18.9 16.7 11.9  6.0  1.6 10.6   40
1802 -1.6  1.6  5.4 10.0 13.0 17.8 18.6 20.6 15.7 12.4  5.3  1.9 10.1   40
1803 -2.5 -0.9  4.0 11.3 12.8 17.2 20.6 20.0 13.8  9.8  5.0  1.2  9.4   42
1804  2.3 -0.5  2.2  8.5 15.3 18.0 19.5 18.7 16.3 10.6  4.0 -1.3  9.5   41
1805 -2.0 -0.1  3.5  7.2 12.2 15.9 18.4 18.0 15.4  6.9  2.1  0.9  8.2   42
1806  1.7  2.3  3.8  6.8 15.0 16.7 18.3 18.6 15.9  9.8  6.0  4.3  9.9   46
1807 -0.7  1.6  1.1  6.6 13.7 16.6 20.7 21.9 13.9 10.8  5.4  1.2  9.4   47
1808 -0.4 -1.0 -0.1  6.1 14.9 17.0 20.6 19.6 15.3  8.5  4.0 -2.9  8.5   48
1809 -3.0  1.8  2.4  5.2 14.1 16.9 18.7 18.9 14.6  8.9  2.8  2.4  8.6   49
1810 -2.0 -0.8  3.8  7.2 12.4 15.8 18.6 18.3 16.1  9.3  4.2  1.7  8.7   49
1811 -3.1  0.8  5.8  8.7 16.0 19.4 20.6 18.4 14.8 11.4  5.0  0.6  9.9   51
1812 -3.6  0.9  1.7  5.0 12.9 16.5 17.8 18.2 13.2 10.0  2.0 -4.4  7.5   52
1813 -3.6  1.6  3.1  9.3 13.9 16.2 18.5 17.7 14.6  9.1  4.5  0.3  8.8   58
1814 -3.7 -3.5  1.8  9.6 11.1 16.1 19.8 18.1 13.3  8.5  4.7  1.7  8.1   56
1815 -3.9  1.6  4.8  8.7 13.9 16.6 17.6 17.6 14.2 10.0  2.7 -1.6  8.5   55
1816 -1.5 -2.8  1.7  7.7 11.9 15.7 17.5 16.7 13.9  9.1  3.2  0.2  7.8   60
1817  1.0  2.2  3.2  5.5 13.0 17.6 18.5 18.0 15.0  6.8  4.7 -1.6  8.7   68
1818  0.0  0.0  3.9  8.5 12.7 17.7 19.6 17.0 14.3  9.6  5.3  0.0  9.1   73
1819  0.3  0.7  3.7  8.9 13.4 17.7 19.5 19.1 15.5  9.2  3.1 -1.6  9.1   74
1820 -4.6  0.1  2.7  9.9 14.1 16.3 18.8 19.5 14.0  9.1  2.6 -1.4  8.4   83
1821 -0.8 -0.9  3.2  9.6 13.2 15.2 17.5 18.2 15.4 10.0  5.7  1.9  9.0   88
1822 -0.4  2.3  6.7  9.9 15.1 19.2 19.9 18.7 14.8 10.8  5.7 -1.6 10.1   88
1823 -5.4 -0.9  3.6  7.6 13.8 16.9 18.6 19.1 14.9  9.6  3.2  0.7  8.5   95
1824 -0.8  0.2  2.8  7.5 12.4 16.4 18.9 18.4 15.6  9.3  4.6  2.2  9.0  102
1825  0.0 -0.2  2.5  9.2 13.7 17.6 19.5 18.7 15.5  9.6  5.4  2.5  9.5  107
1826 -4.9  0.2  3.6  8.0 13.7 18.2 21.2 20.4 15.5 10.4  3.6  1.3  9.3  105
1827 -2.8 -3.2  4.1  9.7 14.5 18.0 20.1 18.1 14.9 10.1  2.0  1.1  8.9  112
1828 -2.2 -1.0  3.8  8.5 13.9 18.4 20.0 18.2 14.4  9.1  4.1  0.6  9.0  120
1829 -4.6 -3.9  1.3  7.8 13.4 16.9 19.2 17.6 14.0  8.0  0.8 -4.3  7.2  132
1830 -6.1 -3.2  3.5  9.3 13.3 17.2 19.9 18.5 13.7  8.9  5.5 -0.1  8.4  135
1831 -4.5 -1.3  3.0  9.3 13.3 17.5 19.7 18.5 13.7 10.9  3.2 -1.4  8.5  141
1832 -2.2 -0.8  2.4  7.5 11.8 16.6 18.2 18.4 13.7  9.6  2.9 -0.7  8.1  142
1833 -2.9  0.9  2.0  7.7 15.3 17.8 18.6 16.5 14.1  9.0  4.1  1.5  8.7  142
1834 -0.8  0.4  3.5  7.7 14.6 17.8 21.3 20.0 15.7  9.2  3.8 -0.1  9.4  145
1835 -0.5  0.1  2.9  7.3 12.9 17.4 19.5 17.7 14.2  9.1  1.5 -3.2  8.2  139
1836 -2.6 -1.4  4.4  7.8 11.4 16.9 18.6 17.3 13.7  9.0  2.4 -0.3  8.1  149
1837 -2.8 -1.2  0.3  6.1 11.8 17.0 18.3 19.0 13.8  8.8  3.8 -1.0  7.8  157
1838 -6.3 -4.9  2.2  6.0 12.6 17.2 19.3 17.6 15.0  8.2  2.4 -1.5  7.3  158
1839 -2.7 -1.3 -0.1  6.1 13.3 17.6 20.2 18.2 14.8  9.8  3.2 -2.6  8.0  166
1840 -3.0 -1.3  0.9  8.4 13.0 17.3 19.1 18.5 14.4  7.7  3.9 -4.2  7.9  174
1841 -3.0 -3.6  2.8  7.9 14.7 17.5 19.1 18.8 15.3  9.7  3.5  0.6  8.6  178
1842 -3.8 -0.9  3.5  7.4 13.3 17.1 19.0 19.5 14.3  7.9  2.1  0.1  8.3  177
1843  0.0  0.0  1.1  7.9 12.2 16.8 19.0 18.9 15.0  8.9  3.4  0.9  8.7  179
1844 -3.0 -2.1  1.9  9.0 13.9 17.3 18.7 17.8 15.0  9.3  3.3 -2.7  8.2  183
1845 -0.6 -3.7  0.3  8.3 12.2 18.0 20.1 18.2 14.2  9.1  4.8 -0.6  8.4  184
1846 -1.2 -0.5  4.3  8.7 13.8 18.3 20.7 20.6 16.1 10.1  3.6 -1.9  9.4  174
1847 -3.3 -1.6  1.0  6.9 14.1 17.0 20.2 19.6 14.7  8.8  4.7 -0.9  8.4  176
1848 -5.8  0.2  3.2  9.2 13.9 18.1 19.5 18.5 14.1  9.7  2.9 -0.2  8.6  183
1849 -2.8  0.0  2.8  7.0 13.4 17.7 19.3 18.5 14.4  9.9  5.1 -1.2  8.7  191
1850 -4.2  1.2  2.0  8.1 13.0 18.1 20.0 19.5 14.6  8.8  4.9  0.4  8.9  191
1851 -0.2  0.2  3.2  8.8 12.8 17.5 19.2 18.9 15.1 10.8  3.7  0.3  9.2  212
1852 -0.5  0.1  2.6  6.8 14.1 17.9 20.5 19.2 15.5  9.9  5.3  3.2  9.6  219
1853  1.1 -0.4  2.1  8.1 13.8 18.1 20.3 19.2 15.4 10.8  4.9 -0.7  9.4  212
1854 -1.1  0.2  4.4  8.9 14.6 17.7 21.0 19.7 15.9 11.4  4.2  1.8  9.9  223
1855 -1.3 -2.5  3.1  9.3 14.0 18.1 20.5 19.8 15.8 11.4  4.9 -1.4  9.3  232
1856 -0.6  0.3  2.0  9.4 13.2 18.6 19.8 19.2 15.2 10.6  3.3  0.9  9.3  256
1857 -2.0  1.3  3.7  8.0 13.4 17.7 20.2 20.0 16.1 11.3  5.0  3.2  9.8  266
1858  0.1 -1.2  3.8  9.3 13.7 19.3 20.1 19.3 16.5 11.6  3.1  2.0  9.8  265
1859  1.0  2.8  6.2  9.1 14.6 18.1 20.8 19.9 15.4 10.8  5.7  0.1 10.4  266
1860  1.1 -0.1  3.3  8.6 14.2 17.8 19.1 18.8 15.3 10.5  4.4 -0.1  9.4  245
1861 -2.3  2.7  5.3  8.2 12.5 18.0 19.5 19.2 15.1 11.0  5.2  1.8  9.7  259
1862 -1.1 -0.4  4.4  9.0 14.0 16.6 18.7 18.1 15.2 10.6  4.0  0.7  9.1  252
1863  2.1  1.8  4.0  8.8 13.7 16.8 18.5 18.8 14.6 10.3  5.5  1.8  9.7  253
1864 -1.5  0.9  4.5  8.2 13.0 17.6 19.3 18.0 14.9  9.0  3.9 -0.2  9.0  276
1865  0.5 -0.3  3.0 10.1 14.7 17.2 19.8 18.3 16.8 10.5  6.6  1.9  9.9  280
1866  2.3  2.2  4.1 10.0 12.5 17.9 19.4 17.8 15.8 10.6  6.1  2.2 10.1  313
1867 -0.3  3.4  2.7  9.1 12.2 17.5 18.8 19.1 15.8 10.9  5.8  0.8  9.7  317
1868 -0.5  1.6  5.6  8.7 14.8 17.9 20.7 19.4 15.6 10.6  5.2  2.8 10.2  327
1869  2.0  4.1  3.9 10.0 13.7 16.9 19.7 19.0 16.1  9.9  5.5  2.3 10.3  320
1870  1.8  0.8  4.0 10.1 14.9 18.5 20.7 19.0 16.1 11.3  6.7  0.5 10.4  350
1871  0.2  1.5  7.0 10.4 14.0 17.6 20.1 20.0 15.5 11.4  4.9  0.7 10.3  388
1872  1.4  2.2  4.5 10.5 14.9 18.6 20.7 19.9 16.6 11.5  6.0  1.5 10.7  419
1873  1.1  1.3  5.2  9.0 13.7 18.7 20.7 20.1 16.0 11.2  5.6  3.2 10.5  434
1874  2.5  2.0  4.9  9.1 14.1 18.5 20.7 19.5 17.0 12.1  6.1  2.3 10.7  444
1875 -0.3 -0.2  3.8  9.1 15.0 18.6 20.3 19.8 16.2 11.1  5.5  2.7 10.1  459
1876  2.5  3.3  5.4 10.5 14.2 19.1 21.1 20.3 16.5 11.9  6.5  1.5 11.1  463
1877  1.6  4.6  5.4 10.2 14.0 18.8 20.7 20.3 16.6 12.0  8.0  5.3 11.5  485
1878  2.9  5.0  8.5 12.6 15.3 18.9 21.4 20.9 17.8 13.2  8.0  2.7 12.3  533
1879  1.4  2.9  6.8 10.6 15.2 18.6 20.7 20.4 17.0 13.7  7.1  2.3 11.4  554
1880  3.9  4.1  6.4 11.1 15.9 18.9 20.9 20.4 17.5 12.1  6.0  3.0 11.7  562
1881  0.0  2.4  5.9 10.2 15.9 18.2 21.2 20.6 17.6 11.9  7.1  4.5 11.3  605
1882  2.8  4.1  6.9 10.7 14.6 18.8 20.7 20.6 17.3 12.7  6.5  2.0 11.5  674
1883 -0.3  1.6  4.2 10.5 14.7 19.4 20.9 20.1 16.9 12.0  6.9  2.6 10.8  704
1884  0.1  2.1  5.1  9.8 14.9 18.6 20.5 20.1 17.5 12.5  6.1  1.7 10.8  753
1885 -1.0  0.6  4.2 10.1 14.5 18.6 21.1 19.7 16.7 11.4  6.5  2.7 10.4  785
1886 -0.9  0.8  4.5 11.2 15.4 18.7 21.1 20.6 17.4 12.4  6.1  1.5 10.7  827
1887 -0.3  1.4  5.0 10.1 16.0 19.1 21.8 20.1 17.1 11.3  6.4  1.9 10.8  871
1888 -1.0  1.3  3.9 10.9 14.9 19.0 21.0 20.3 17.0 11.7  6.8  3.0 10.7  946
1889  1.0  1.0  6.0 11.2 15.8 19.1 21.2 20.4 16.8 11.8  6.6  4.0 11.2 1037
1890  1.5  2.5  5.2 11.0 15.1 19.5 21.4 20.4 17.2 12.0  7.1  1.8 11.2 1078
1891 -0.1  0.6  4.1 10.3 14.8 18.9 20.6 20.4 17.7 11.7  5.3  3.1 10.6 1169
1892 -0.8  1.9  4.1  9.9 14.6 19.4 21.2 20.9 17.6 12.1  5.6  0.2 10.6 1259
1893 -2.9 -0.2  4.7 10.0 14.7 19.5 21.7 20.7 17.1 12.2  5.7  1.7 10.4 1340
1894  0.0  0.6  6.4 11.0 15.5 19.5 21.8 21.0 17.3 12.2  5.9  2.1 11.1 1394
1895 -1.3 -1.2  4.6 11.2 15.5 19.4 20.9 20.8 18.0 11.3  5.9  1.7 10.6 1474
1896  0.0  1.9  4.1 10.9 16.3 19.7 21.7 21.0 16.8 11.7  5.2  2.3 11.0 1512
1897 -0.5  1.5  4.8 10.8 15.6 19.3 21.9 20.8 18.2 12.7  5.7  0.9 11.0 1582
1898  1.5  1.9  5.2 10.2 15.4 19.5 21.6 21.3 17.9 11.6  5.7  1.4 11.1 1623
1899  0.5 -0.7  4.0 10.8 15.4 19.3 21.4 20.9 17.3 12.7  7.9  1.4 10.9 1656
1900  0.9  0.6  4.7 10.8 15.7 19.5 21.3 21.5 17.8 13.7  6.4  2.6 11.3 1697
1901  0.4  0.2  5.7 10.6 15.5 19.5 22.4 21.1 17.0 12.6  6.1  1.4 11.0 1713
1902  0.8  1.1  6.3 10.4 15.6 18.7 20.9 20.3 16.7 12.2  7.1  0.9 10.9 1756
1903  0.8  1.5  6.7 10.5 15.2 18.1 20.7 20.0 16.8 12.2  5.8  0.9 10.8 1807
1904 -0.7  0.5  5.3 10.0 15.3 18.7 20.7 20.2 17.1 12.3  7.1  1.8 10.7 1847
1905 -0.5 -0.3  6.8 10.5 15.3 19.2 21.1 20.8 17.8 11.7  7.2  2.6 11.0 1885
1906  2.3  1.9  4.5 11.9 15.7 19.2 21.2 21.0 17.9 12.3  6.5  2.8 11.4 1926
1907  1.2  2.3  7.4  9.6 14.0 18.1 20.7 20.1 17.3 12.6  6.9  3.4 11.1 2056
1908  2.1  2.4  6.5 11.4 15.3 18.6 20.9 20.1 17.7 12.1  7.2  3.0 11.4 2082
1909  1.2  2.8  5.7 10.2 14.6 18.9 20.5 20.8 17.3 12.3  8.2  1.0 11.1 2128
1910  1.6  1.6  8.7 12.0 14.9 18.7 21.1 20.1 17.4 13.0  6.4  2.1 11.5 2177
1911  1.3  2.4  6.6 10.7 15.9 19.4 20.9 20.2 17.7 12.3  6.2  3.3 11.4 2229
1912 -0.6  2.1  4.8 11.1 15.5 18.5 20.5 19.6 16.5 12.0  7.1  3.2 10.9 2262
1913  1.7  1.5  5.9 11.6 14.9 18.6 20.7 20.7 16.9 12.0  8.4  3.9 11.4 2326
1914  2.8  1.8  6.5 11.0 15.8 19.1 21.1 20.3 17.0 13.1  7.4  1.3 11.4 2377
1915  0.8  3.6  5.0 12.3 14.5 18.0 20.2 19.6 17.1 12.5  7.3  2.6 11.1 2392
1916  0.6  2.0  5.4 10.6 14.7 17.8 21.1 20.2 16.5 11.7  6.4  0.9 10.7 2405
1917  0.0  0.1  4.8  9.9 13.2 18.0 20.9 19.8 16.7 10.8  7.2  0.2 10.1 2426
1918 -1.2  1.9  7.1 10.2 15.0 18.8 20.1 20.3 16.1 13.2  6.9  3.2 11.0 2448
1919  1.9  2.0  5.8 11.0 14.8 19.0 20.9 20.1 17.5 12.1  6.0  1.3 11.0 2449
1920  0.7  2.6  6.4  9.8 14.9 18.4 20.5 20.0 17.3 12.8  6.5  2.9 11.1 2459
1921  3.0  3.8  8.1 11.6 15.6 19.5 21.5 20.1 17.8 12.9  6.9  3.5 12.0 2523
1922  0.3  2.2  6.4 11.2 15.8 19.2 20.5 20.4 17.8 12.8  7.4  2.7 11.4 2548
1923  2.3  1.2  5.4 10.4 14.9 18.6 20.7 19.9 17.3 12.2  7.7  4.3 11.2 2590
1924  0.0  2.6  5.2 10.5 14.4 18.5 20.4 20.2 16.6 12.9  7.2  0.9 10.8 2624
1925  0.7  3.8  6.8 12.0 14.9 19.0 20.7 20.2 17.6 10.7  6.7  2.8 11.3 2660
1926  1.7  3.8  5.8 10.3 15.2 18.3 20.6 20.3 16.8 12.3  6.6  1.7 11.1 2712
1927  0.9  3.1  6.3 10.7 14.6 18.2 20.7 19.5 17.2 13.1  7.2  0.6 11.0 2713
1928  1.5  2.4  5.9  9.9 15.3 17.7 20.8 20.2 16.7 12.5  7.1  2.8 11.1 2718
1929 -0.8 -0.5  6.4 10.4 14.6 18.2 20.6 20.3 16.6 12.4  6.2  2.0 10.5 2752
1930 -0.7  3.6  6.0 11.5 15.0 18.7 21.3 20.7 17.2 11.7  6.9  2.3 11.2 2779
1931  2.1  3.3  5.9 11.0 15.0 19.3 21.4 20.4 18.1 13.3  7.9  3.8 11.8 2875
1932  2.8  2.8  4.9 11.3 15.4 18.9 20.8 20.6 17.3 12.3  6.5  2.3 11.3 2911
1933  2.1  1.5  6.0 10.8 15.3 19.5 21.2 20.3 17.8 12.5  6.8  2.4 11.3 2946
1934  2.3  2.6  6.2 11.4 16.6 19.3 21.5 20.5 16.9 13.0  8.1  2.7 11.8 2965
1935  0.7  3.8  6.8 10.4 14.3 18.4 21.3 20.5 17.0 12.6  6.0  1.9 11.1 2980
1936 -0.3 -1.0  5.9 10.1 15.8 19.1 21.7 20.8 17.3 12.0  6.2  2.8 10.9 3045
1937 -0.4  1.5  4.7 10.3 15.5 18.9 21.1 21.0 17.3 12.2  6.2  1.5 10.8 3074
1938  0.8  2.2  7.0 11.3 15.2 18.6 20.9 20.7 17.5 13.0  6.5  1.7 11.3 3103
1939  1.3  1.2  5.4 10.6 15.6 18.7 21.0 20.3 17.2 11.7  6.5  3.7 11.1 3140
1940 -1.8  1.5  5.4 10.4 14.8 18.7 20.9 20.1 17.1 12.3  5.8  2.8 10.7 3176
1941  0.7  2.0  5.3 11.2 15.4 18.6 20.8 19.9 16.7 12.6  6.8  2.8 11.1 3273
1942  0.8  1.1  6.0 11.2 14.9 18.5 20.6 19.9 16.7 12.4  6.7  1.8 10.9 3283
1943 -0.2  2.8  5.1 11.0 15.0 18.4 20.7 20.1 16.7 12.4  6.4  2.6 10.9 3322
1944  2.0  2.5  5.3 10.1 15.5 18.5 20.4 19.9 17.1 12.4  6.5  1.2 11.0 3330
1945  0.1  1.8  6.8 10.7 14.1 17.8 20.0 20.1 16.8 12.1  6.3  0.9 10.6 3378
1946  1.4  2.6  7.1 11.5 14.6 18.2 20.5 19.7 16.8 11.9  6.6  2.1 11.1 3430
1947  0.8  1.1  5.5 10.8 14.8 18.0 20.3 20.4 17.1 13.3  6.1  2.2 10.9 3492
1948  0.8  1.6  5.2 11.2 15.2 18.7 20.4 19.9 17.1 12.1  7.0  2.2 10.9 3652
1949  1.5  2.3  6.2 11.3 15.7 18.8 20.7 20.3 16.9 12.9  7.9  3.0 11.5 3940
1950  1.2  3.1  6.2 10.8 15.5 18.7 20.2 19.7 17.0 13.2  6.8  3.2 11.3 4029
1951  2.8  3.9  7.0 12.1 16.2 18.8 20.9 20.6 17.8 13.5  8.0  4.9 12.2 4701
1952  4.0  5.1  7.1 12.7 16.2 19.6 21.3 20.7 18.0 13.2  8.2  4.8 12.6 4865
1953  4.2  5.2  8.8 12.5 16.4 19.8 21.2 20.8 18.1 14.3  8.9  5.5 13.0 4963
1954  2.7  5.3  7.6 12.6 15.8 19.4 21.0 20.6 18.2 13.8  9.4  4.9 12.6 5057
1955  3.9  4.6  7.5 12.6 16.4 19.1 21.2 20.9 18.0 13.9  7.8  4.3 12.5 5053
1956  3.3  3.6  7.5 11.9 16.1 19.3 20.6 20.1 17.4 13.7  8.0  4.9 12.2 5095
1957  2.6  4.9  7.6 12.3 16.1 19.4 20.9 20.3 17.5 13.0  8.5  5.4 12.4 5091
1958  3.6  4.3  7.2 12.2 16.4 18.9 20.7 20.3 17.4 13.3  8.6  4.3 12.3 5114
1959  2.9  4.3  8.2 12.4 16.1 19.3 21.0 20.5 17.4 13.0  7.6  4.9 12.3 5157
1960  3.2  4.8  6.6 12.2 15.8 19.2 20.7 20.3 17.7 13.5  8.6  4.7 12.3 5241
1961  3.9  6.0  9.1 12.6 16.2 19.5 20.7 20.5 17.8 13.8  9.1  4.9 12.8 5439
1962  4.1  5.6  8.1 12.8 16.5 19.0 20.5 20.3 17.6 14.2  9.3  5.4 12.8 5556
1963  2.9  5.2  8.5 12.7 16.4 19.1 20.9 20.4 18.1 14.7  9.7  4.5 12.8 5657
1964  4.2  4.7  7.9 12.6 16.5 19.1 20.8 19.9 17.4 13.5  9.1  4.9 12.6 5692
1965  4.3  4.8  7.8 12.3 16.2 18.9 20.2 19.9 17.3 13.8  9.1  6.0 12.6 5852
1966  3.5  5.5  8.9 12.5 16.0 19.1 20.8 20.1 17.5 13.8  9.3  5.2 12.7 5912
1967  4.2  4.9  8.8 12.7 16.1 18.9 20.5 20.2 17.5 14.2  9.1  5.3 12.7 5926
1968  3.7  5.0  9.6 12.9 15.9 18.9 20.4 19.8 17.5 13.8  9.2  5.0 12.6 5943
1969  3.3  4.6  7.8 12.8 16.4 18.7 20.5 20.2 17.6 13.6  9.4  5.7 12.5 5977
1970  3.6  5.9  8.1 12.8 16.3 19.1 20.7 20.2 17.6 13.5  9.1  5.2 12.7 5984
1971  4.0  5.2  7.9 12.3 15.8 18.7 20.2 19.9 17.5 13.8  9.1  5.6 12.5 5874
1972  3.3  4.5  8.7 12.4 16.1 18.8 20.3 19.9 17.1 13.1  8.5  5.2 12.3 5871
1973  4.3  5.9  9.2 12.6 16.1 19.1 20.6 20.2 17.5 13.7  8.6  5.2 12.8 5929
1974  3.8  5.2  8.7 12.6 15.8 18.6 20.4 19.8 17.0 13.2  8.8  5.2 12.4 5935
1975  4.5  5.0  8.2 12.2 16.2 18.8 20.5 19.9 17.4 13.5  8.8  4.8 12.5 5951
1976  3.4  5.3  7.7 12.3 15.5 18.4 19.9 19.3 16.8 12.1  7.8  4.1 11.9 5797
1977  2.0  5.4  9.0 12.9 16.2 18.8 20.4 19.7 17.2 13.2  9.1  4.6 12.4 5776
1978  3.3  4.2  8.3 12.2 15.8 18.5 20.2 19.6 17.3 13.3  8.6  4.6 12.2 5776
1979  2.8  3.8  8.5 11.7 15.7 18.7 20.1 19.8 17.4 13.6  8.7  6.0 12.2 5726
1980  3.3  4.6  7.6 12.2 15.9 18.7 20.4 19.9 17.2 13.2  9.0  4.7 12.2 5704
1981  3.2  4.9  8.4 12.4 15.3 18.6 20.3 19.8 17.0 12.7  8.0  4.5 12.1 5440
1982  1.1  3.3  6.7 11.1 15.6 17.8 19.9 19.5 16.9 12.7  7.5  4.7 11.4 5171
1983  3.2  4.4  7.7 11.4 15.2 18.0 20.3 20.3 17.2 13.1  8.3  2.7 11.8 5130
1984  2.4  4.2  6.7 11.1 15.3 18.4 20.1 19.9 16.4 12.7  7.3  3.0 11.5 5040
1985  1.0  2.5  6.9 12.1 15.7 18.0 20.1 19.8 16.5 12.5  6.8  2.2 11.2 4982
1986  3.0  3.1  7.7 12.1 15.8 18.8 20.2 19.7 16.9 12.5  7.0  3.7 11.7 4928
1987  2.9  5.1  7.1 12.2 16.1 19.1 20.8 20.0 17.5 12.8  8.3  4.8 12.2 4846
1988  3.2  3.7  7.8 12.2 16.1 19.2 21.1 20.6 17.4 12.9  8.1  4.6 12.2 4805
1989  3.9  4.2  8.0 12.4 15.9 18.6 20.6 20.0 17.1 13.1  7.8  3.2 12.1 4723
1990  5.7  6.9 10.5 13.3 16.4 19.5 21.3 21.0 18.7 14.9 11.3  6.9 13.9 4482
1991  6.8  8.8 11.1 14.1 17.2 19.6 20.9 20.6 18.4 14.8  9.4  6.6 14.0 3494
1992  6.6  8.1 10.2 13.5 16.8 19.0 20.7 20.1 18.1 14.1  8.5  4.6 13.4 3372
1993  3.5  3.8  7.8 12.4 17.1 19.8 22.0 21.7 18.1 13.8  7.5  5.4 12.7 2945
1994  3.6  4.5  9.4 13.7 16.9 21.2 22.2 21.6 19.2 14.8 10.1  6.8 13.7 2872
1995  4.8  5.7  9.6 12.6 16.6 20.1 22.8 22.7 18.7 14.7  8.8  5.1 13.5 2711
1996  4.2  5.9  7.7 12.6 17.2 20.5 22.0 21.7 18.2 14.0  8.0  5.6 13.1 2815
1997  3.2  6.2  9.7 11.9 16.5 20.2 22.0 21.6 18.9 14.1  8.7  5.5 13.2 2766
1998  5.2  7.4  8.7 13.3 17.9 20.4 22.7 22.2 19.9 14.6  9.7  5.8 14.0 2731
1999  4.6  6.7  8.6 13.3 17.1 20.3 22.6 21.9 18.7 14.1 10.1  5.7 13.6 2741
2000  3.8  6.5  9.7 13.1 17.4 20.3 21.8 22.0 18.6 14.1  7.4  3.2 13.2 2702
2001  3.3  4.6  8.5 13.1 17.2 20.3 22.2 22.4 18.6 14.5 10.4  5.7 13.4 2727
2002  5.1  6.1  8.6 13.6 16.6 20.9 22.9 21.9 19.4 13.5  9.1  5.5 13.6 2698
2003  4.0  4.4  8.9 13.1 17.2 20.3 22.5 22.4 18.5 14.7  9.4  5.6 13.4 2669
2004  3.0  5.3 10.1 13.4 17.4 20.2 21.9 21.2 19.1 14.7 10.0  5.9 13.5 2663
2005  5.0  6.3  8.9 13.9 16.9 20.8 22.7 22.1 19.7 14.9 10.3  4.4 13.8 2591
2006  5.3  5.1  8.8 14.3 17.1 19.7 21.4 20.5 18.7 15.6 11.3  8.7 13.9 2538
2007  8.3  8.2 11.2 14.6 17.5 19.9 20.9 20.8 18.8 15.5 10.8  8.5 14.6 1491
2008  8.0  9.1 12.7 15.3 17.7 20.0 21.5 21.0 18.5 15.4 11.6  8.2 14.9 1612
2009  7.2  8.8 11.3 15.1 17.8 20.1 21.2 20.9 18.4 14.8 11.5-99.0 15.2 1595
AA    2.5  3.9  7.3 11.8 15.8 18.9 20.8 20.3 17.4 13.1  7.9  3.9 12.0
Ad    0.2  1.6  4.8  9.6 14.1 17.7 19.6 19.0 15.8 10.8  5.6  1.9 10.1
 
For Country Code ALL
 
From input file /gnuit/GIStemp/STEP0/to_next_step/v2.mean_comb

v3

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
--------------------------------------------------------------------------
1701 -4.2 -1.5  1.6-99.0-99.0 15.4 18.9 15.8-99.0-99.0-99.0 -0.5  6.5    1
1702  2.0 -0.5  0.6  2.6 10.9 16.0 16.0 15.8 10.1  7.5  0.2  0.6  6.8    1
1703 -2.8 -0.9  0.6  7.7 14.1 16.1 15.4 16.3 11.4  6.1  2.2  2.5  7.4    1
1704 -4.9 -0.5  3.9  9.4 11.8 14.1 17.1-99.0-99.0-99.0-99.0 -0.9  6.2    1
1705 -7.1-99.0  1.0-99.0-99.0 16.0 18.3 17.8  8.7  7.5  0.7  1.8  7.2    1
1706 -1.2 -1.0  2.8  7.4 12.8 17.2 16.6 15.6 11.8  8.5  3.5  2.5  8.0    2
1707 -0.5  0.9  2.5  6.4 11.7 17.2 18.0 15.6 12.6  6.0  3.8  1.8  8.0    2
1708  3.0  0.9  4.8  7.8 11.1 14.3 13.7 18.0 14.3  4.7  3.3 -1.6  7.9    2
1709 -9.0 -3.9  0.9  9.4 11.7 16.7 16.0 16.0 12.2  8.1  5.6  2.0  7.2    2
1710 -1.1 -0.2  4.2  6.9 12.9 15.2 15.2 16.5 13.8  9.4  7.4  6.5  8.9    2
1711  3.5  0.0  4.7  9.5 12.2 16.9 16.0 15.6 13.3  9.3  6.5  1.5  9.1    1
1712  0.2  2.9  4.1  7.7 12.3 16.3 16.8 14.9 13.1  9.5  5.0  4.2  8.9    1
1713 -0.3  5.0  1.0  5.3 10.5 13.6 14.8 15.4 13.9  9.3  3.4  2.5  7.9    1
1714  1.9  3.8  5.0  7.9 10.2 14.5 18.5 13.8 13.0  9.7  4.6  2.4  8.8    1
1715  0.7  3.5  5.7  9.6 11.6 14.5 15.8 17.0 14.1 10.3  6.3 -1.5  9.0    1
1716 -5.0  1.5  3.3  9.1 11.3 14.0 16.3 15.5 12.4  8.3  3.9  1.2  7.7    1
1717  0.9  0.7  3.4  7.2 10.2 15.3 15.7 15.5 13.9  9.3  3.4  3.5  8.3    1
1718 -1.6 -0.8  4.6  8.3 12.7 16.0 18.0 19.0 15.1  8.9  5.2  3.3  9.1    1
1719  0.5  2.5  3.5  5.6 13.4 16.0 20.1 18.9 14.1  8.2  5.0  1.3  9.1    1
1720  2.9  2.9  3.1  6.8 12.3 12.6 17.2 14.5 14.3  8.1  5.6  3.6  8.7    1
1721  3.5  0.1  0.8  8.9 10.2 15.3 15.2 16.5 14.4  8.6  5.8  1.9  8.4    1
1722  0.9  3.9  5.5  8.6 11.5 15.1 15.8 15.5 14.6 10.4  6.8  3.3  9.3    1
1723  0.3  2.5  6.4  8.4 12.4 15.6 15.6 15.9 13.9 11.0  2.2  4.7  9.1    1
1724  4.8  3.6  3.7  6.7 11.8 16.7 15.1 16.9 14.2  8.3  5.1  2.0  9.1    1
1725  2.3  0.4  3.5  7.0 10.6 14.0 14.6 14.3 12.5  8.0  3.0  2.0  7.7    1
1726 -1.8  0.2  2.5  7.8 14.1 16.2 15.6 14.4 14.2  9.2  5.3  0.1  8.1    1
1727  2.6  3.6  3.7  7.0 15.0 15.4 16.8 17.5 14.7 11.5  3.6  2.5  9.5    1
1728  2.5 -0.6  6.9  8.9 14.8 16.6 16.5 14.6 13.1  9.2  4.3 -0.6  8.9    2
1729 -3.1  0.3  0.2  6.3 11.1 16.2 17.8 17.7 16.9 12.1  5.3  5.3  8.9    2
1730  2.4  2.3  4.3  9.1 12.6 15.6 17.2 16.8 14.4  7.0  7.5  2.2  9.3    2
1731 -0.5 -0.4  3.3  6.4 12.0 15.4 16.5 16.9 14.8 11.9  6.6  3.2  8.8    2
1732 -0.6  3.3  5.3  9.8 12.9 14.2 16.1 16.2 14.1 10.4  4.4 -0.9  8.8    2
1733  4.3  4.5  5.1 10.5 11.5 13.9 18.4 16.5 12.1  8.2  5.5  5.7  9.7    2
1734  1.6  4.4  6.4  9.5 12.4 14.7 17.0 16.4 14.1  9.6  2.0  1.4  9.1    2
1735  3.0  2.5  5.8  9.6 12.2 15.6 16.1 16.5 15.2  7.6  4.1  3.0  9.3    2
1736  1.4  0.8  3.2  9.2 12.2 15.1 17.4 17.7 13.9  9.4  5.7  4.2  9.2    2
1737  4.0  3.0  5.4  7.3 13.8 16.0 16.6 14.5 14.5  8.7  4.3  2.1  9.2    2
1738  0.0  2.5  5.1  9.6 12.8 15.2 16.5 16.0 13.6  9.9  2.0  4.2  9.0    2
1739 -1.4  1.0  3.6  5.2 12.3 14.9 17.7 15.0 13.8  5.8 -0.9  1.9  7.4    3
1740 -6.4 -5.4  0.6  4.9  7.8 13.2 16.0 15.5 13.9  4.3  1.5  0.5  5.5    3
1741 -2.6  2.3  2.5  5.4  9.4 13.8 17.1 15.8 12.9  9.7  5.8  1.4  7.8    3
1742 -2.8  2.2  1.5  4.9  9.7 14.9 15.9 14.5 10.9  8.1  3.6 -2.5  6.7    3
1743  1.2  1.8  2.6  4.9 12.4 18.0 17.8 17.0 14.4  4.4  4.6 -0.1  8.2    5
1744 -3.8 -3.1  0.2  6.9 11.8 16.0 18.2 14.7 13.5  7.9  3.8 -1.4  7.1    5
1745 -3.1 -3.7 -0.1  6.7 12.8 17.0 18.0 16.8 16.1  8.5  4.8 -0.3  7.8    5
1746 -0.5 -0.4 -0.8  6.6 13.0 15.6 17.9 15.2 13.2  6.4  1.5  3.1  7.6    4
1747 -1.5 -0.3 -0.5  7.2 11.2 18.5 18.2 15.8 15.2  9.5  4.4  1.0  8.2    4
1748 -1.5 -1.5 -2.3  6.7 13.4 17.3 17.6 18.2 14.2  8.6  4.7  3.5  8.2    4
1749 -0.1 -1.3  0.5  6.6 13.3 15.2 17.1 17.1 13.8  7.8  3.6  0.9  7.9    4
1750 -0.5  1.4  4.4  7.3 12.1 15.7 19.1 17.6 13.6  6.2 -0.6 -0.9  8.0    5
1751 -1.5 -3.5  3.5  6.4 12.8 16.0 17.9 17.4 12.2 11.1 -5.0-14.1  6.1    6
1752 -5.8 -3.7  1.0  4.4  9.8 15.3 19.4 17.6 11.4  7.3  3.8 -0.9  6.6    5
1753 -3.3 -1.7  3.5  7.0 11.7 16.5 18.3 17.0 13.7  9.4  2.4 -3.7  7.6    8
1754 -2.6 -3.1 -0.6  6.5 12.6 16.5 17.3 17.1 13.1  9.2  3.5 -0.2  7.4    8
1755 -5.3 -4.7  0.5  8.9 11.9 17.9 18.9 16.1 12.7  8.1  3.1 -0.0  7.3   10
1756  0.2  1.6  2.4  5.5 10.5 17.7 18.9 16.3 14.0  8.1  0.9 -2.2  7.8   11
1757 -3.7 -0.2  2.5  8.4 12.1 18.0 21.6 18.4 13.5  5.5  4.2 -1.6  8.2   13
1758 -4.2 -1.2  2.8  7.0 13.8 17.3 17.5 18.0 12.5  6.7  4.2  0.1  7.9   13
1759  1.0  2.3  3.9  8.1 12.2 17.7 20.4 18.8 14.7 10.0  2.2 -2.5  9.1   14
1760 -3.8 -0.5  1.6  8.0 12.8 17.3 19.0 17.5 15.2  8.8  4.0  1.3  8.4   14
1761 -1.7  1.0  5.2  7.4 13.7 18.1 19.0 18.9 15.2  6.8  3.6 -2.3  8.7   14
1762  1.2  0.2  0.8 10.0 13.3 17.1 19.0 16.3 13.6  6.2  3.6 -1.2  8.3   13
1763 -4.1  2.3  2.4  7.2 11.4 16.4 18.9 18.7 13.4  7.9  4.3  2.3  8.4   15
1764  2.3  3.8  3.5  7.6 13.6 15.9 19.6 17.0 13.1  8.5  3.8  0.9  9.1   16
1765  1.1 -1.4  5.3  8.6 12.0 16.4 17.3 18.1 13.9  9.7  4.4 -0.2  8.8   16
1766 -3.0 -0.4  4.1  9.7 13.0 17.5 18.9 18.4 15.0  9.4  5.7 -0.2  9.0   16
1767 -5.6  2.6  4.1  6.6 11.6 15.9 18.1 18.7 14.9  9.4  6.5 -0.9  8.5   17
1768 -3.2  0.4  2.1  7.8 12.8 16.5 19.0 18.2 12.9  7.9  3.7  0.2  8.2   20
1769 -0.8 -0.9  2.4  7.5 12.1 16.3 18.5 17.0 14.2  6.1  4.2  1.0  8.1   21
1770 -1.3  0.9  0.5  6.8 12.8 16.3 18.4 18.7 15.6  9.4  4.1  1.8  8.7   21
1771 -1.4 -1.6  0.8  5.1 14.6 17.3 18.7 17.5 14.4  9.9  3.2  2.2  8.4   22
1772 -1.1  0.5  3.3  7.4 11.0 17.8 18.9 18.3 15.1 11.3  6.7  2.3  9.3   21
1773  0.9 -0.5  3.6  8.7 14.1 16.6 18.6 18.8 15.3 10.9  4.7  2.5  9.5   23
1774 -2.1  1.4  5.1  9.8 13.2 17.9 18.9 18.8 13.8  8.8 -0.1 -2.3  8.6   21
1775 -1.5  2.3  4.2  7.2 12.2 18.2 19.8 19.4 15.7  9.5  3.0 -0.4  9.1   23
1776 -8.0  0.3  3.1  7.0 10.3 17.2 19.5 18.2 13.2  8.4  3.0 -0.9  7.6   24
1777 -3.5 -2.8  3.0  5.5 12.4 15.9 17.4 18.3 13.4  8.4  4.0 -1.9  7.5   25
1778 -2.9 -1.7  2.1  8.8 13.4 16.3 20.3 18.6 12.6  6.6  3.2  1.0  8.2   24
1779 -5.0  1.6  4.4  9.6 14.1 15.5 18.5 19.1 15.4 10.4  3.3  0.2  8.9   27
1780 -5.4 -3.2  5.1  6.1 13.9 16.7 19.1 18.7 13.9  9.9  2.8 -1.7  8.0   28
1781 -2.0  0.1  4.2  9.5 13.6 17.8 19.1 19.8 15.2  7.6  4.0 -0.8  9.0   32
1782 -0.9 -4.2  1.2  6.4 11.7 17.4 19.3 17.8 14.1  7.3  0.8 -1.0  7.5   33
1783 -0.8  2.0  1.8  8.4 13.8 17.5 20.1 18.4 14.8  9.6  3.2 -2.0  8.9   32
1784 -4.8 -2.6  1.2  6.0 14.6 16.9 18.6 17.5 15.5  6.7  4.2 -1.6  7.7   33
1785 -1.1 -2.6 -2.4  5.7 12.1 16.5 18.0 17.0 15.2  8.3  4.1 -0.7  7.5   34
1786 -1.5 -0.6  1.0  9.0 12.2 17.4 17.3 17.1 13.3  6.8  0.6 -0.6  7.7   34
1787 -1.7  1.5  4.7  7.0 11.9 17.6 18.1 18.3 14.4 10.7  3.8  1.7  9.0   31
1788  0.1  0.4  3.0  9.0 14.0 18.2 20.9 17.6 15.7  8.6  2.4 -7.9  8.5   33
1789 -3.2  1.3 -0.5  8.7 15.7 16.5 19.4 18.7 14.8  9.3  3.8  1.9  8.9   32
1790  0.6  3.0  4.9  6.6 14.7 17.7 17.6 18.4 13.9  9.9  4.1  1.5  9.4   30
1791  2.0  1.3  4.8 10.6 13.1 17.2 19.3 19.8 14.3  9.3  3.6  1.4  9.7   33
1792 -1.3 -0.4  4.3  9.9 12.9 17.3 19.7 18.6 14.0  9.2  4.3  0.9  9.1   34
1793 -1.9  2.5  4.0  7.4 12.8 16.4 20.7 19.3 14.2 11.1  5.1  2.0  9.5   33
1794  0.2  3.3  6.6 11.6 13.9 17.9 21.1 17.8 13.4  9.4  5.0 -0.1 10.0   34
1795 -6.2 -0.6  3.0 10.3 13.0 17.2 17.3 18.6 15.6 11.8  3.5  3.0  8.9   35
1796  4.7  2.3  2.1  9.0 13.7 17.2 18.9 19.0 16.1  9.5  3.9 -2.0  9.5   37
1797 -0.3  1.8  3.1  9.4 14.7 16.6 20.5 19.5 15.9 10.0  5.1  2.7  9.9   36
1798  0.8  2.5  4.5  9.8 15.0 18.6 20.0 19.9 16.2 10.2  4.3 -1.8 10.0   39
1799 -3.4 -0.9  2.7  7.5 12.5 16.5 18.6 18.5 14.9  9.9  5.3 -2.1  8.3   39
1800  0.1  0.4  1.5 12.7 15.6 15.8 19.0 19.5 15.5 10.1  6.1  2.0  9.9   39
1801  1.8  1.6  6.7  9.5 15.6 16.8 19.4 18.6 16.5 11.6  5.8  1.4 10.4   39
1802 -2.0  1.3  5.2  9.9 12.9 17.9 18.5 20.6 15.6 12.3  5.2  1.8  9.9   39
1803 -2.8 -1.2  3.8 11.2 12.7 17.1 20.5 19.9 13.6  9.6  4.9  1.1  9.2   41
1804  2.4 -0.4  2.4  8.6 15.4 18.1 19.6 18.8 16.5 10.7  4.1 -1.3  9.6   41
1805 -2.0 -0.1  3.6  7.4 12.3 16.0 18.5 18.1 15.5  7.0  2.1  0.9  8.3   42
1806  1.8  2.4  3.9  6.9 15.2 16.9 18.5 18.6 15.9  9.8  6.1  4.4 10.0   46
1807 -0.8  2.1  1.6  6.7 14.1 16.6 20.8 22.0 13.9 10.9  5.5  1.2  9.5   47
1808 -0.5 -1.0 -0.2  6.2 15.1 17.0 20.6 19.6 15.4  8.5  4.1 -3.0  8.5   48
1809 -3.0  1.9  2.5  5.3 14.2 17.0 18.8 18.9 14.6  8.9  2.8  2.4  8.7   49
1810 -2.1 -0.8  3.9  7.3 12.5 16.0 18.7 18.4 16.1  9.4  4.3  1.7  8.8   49
1811 -3.2  0.9  5.9  8.9 16.1 19.5 20.7 18.5 14.9 11.4  5.1  0.6  9.9   51
1812 -3.7  0.3  1.8  5.1 13.0 16.6 17.9 18.3 13.3 10.0  2.0 -4.6  7.5   51
1813 -3.6  1.8  3.3  9.5 14.1 16.1 19.2 17.6 14.5  9.2  4.5  0.7  8.9   56
1814 -3.7 -3.6  1.9  9.8 11.3 16.1 19.9 18.1 13.3  8.5  4.7  1.8  8.2   54
1815 -3.5  1.8  4.9  8.9 14.0 16.8 17.6 17.7 14.2 10.0  2.6 -1.7  8.6   54
1816 -1.1 -2.8  2.2  7.8 12.0 15.8 17.6 16.7 14.0  9.1  3.2  0.2  7.9   59
1817  1.1  2.4  3.3  5.7 13.1 17.7 18.5 18.0 15.1  6.7  4.7 -1.8  8.7   66
1818 -0.1  0.1  4.0  8.7 12.8 17.6 19.5 17.0 14.5  9.6  5.3 -0.1  9.1   71
1819  0.3  0.9  4.0  9.1 13.6 17.7 19.6 19.1 15.6  9.4  3.4 -1.4  9.3   71
1820 -4.2  0.6  3.0 10.1 14.3 16.1 18.6 19.4 13.9  9.1  2.7 -1.1  8.5   77
1821 -0.2 -0.8  3.4 10.3 13.2 14.9 17.4 18.1 15.4 10.1  5.8  2.4  9.2   81
1822 -0.1  2.6  6.8  9.9 14.8 18.9 19.4 18.2 14.2 10.6  5.5 -1.5  9.9   77
1823 -5.7 -0.3  3.7  7.2 13.8 16.6 18.1 18.9 14.7  9.6  3.4  1.0  8.4   85
1824 -0.9  0.6  2.6  7.2 12.0 15.9 18.6 18.0 15.5  9.0  4.8  2.4  8.8   89
1825  0.2 -0.2  1.9  9.0 13.5 17.2 18.9 18.3 15.3  9.4  5.4  2.7  9.3   95
1826 -5.1  0.3  3.8  7.9 13.1 17.8 20.9 20.2 15.1 10.2  3.6  1.6  9.1   94
1827 -2.5 -4.0  4.1  9.6 14.5 18.0 19.9 17.9 14.7 10.0  2.0  1.5  8.8   97
1828 -2.4 -1.5  3.6  8.8 13.8 18.1 19.8 17.6 14.0  8.8  4.0  0.4  8.7  103
1829 -4.9 -3.8  1.3  7.7 12.9 16.4 19.0 16.9 13.8  7.5  0.5 -5.6  6.8  111
1830 -7.0 -3.8  3.1  8.7 12.9 16.6 19.1 17.8 13.0  8.1  4.6 -0.6  7.7  112
1831 -4.7 -0.9  2.7  9.1 12.7 16.6 19.1 17.7 12.9 10.5  2.6 -0.7  8.1  117
1832 -2.5 -0.8  2.3  7.4 11.6 16.0 17.3 17.8 12.7  8.7  1.9 -1.6  7.6  114
1833 -4.1  1.1  1.6  6.8 15.0 17.8 17.7 15.5 13.3  8.5  3.6  1.3  8.2  115
1834 -0.7 -0.6  3.0  6.8 14.6 17.4 20.7 19.5 15.2  8.8  3.3 -0.1  9.0  116
1835 -0.6  0.9  3.0  6.9 12.2 16.7 19.0 17.0 13.8  8.2  0.5 -3.6  7.8  112
1836 -2.9 -0.9  5.3  7.8 10.9 16.6 18.0 16.8 13.0  9.6  2.4  0.2  8.1  117
1837 -2.5 -1.2  0.1  5.9 11.4 16.6 17.4 18.6 13.2  8.5  3.3 -1.4  7.5  123
1838 -8.0 -4.6  1.7  5.9 12.6 16.3 18.4 16.8 14.5  7.9  2.5 -1.3  6.9  128
1839 -2.9 -1.6 -0.9  5.0 13.0 17.6 19.7 17.8 14.5  9.2  3.2 -3.0  7.6  137
1840 -2.4 -2.0  0.1  7.8 12.3 16.8 18.3 17.8 13.9  7.2  3.8 -5.0  7.4  141
1841 -3.5 -3.8  2.8  8.1 14.9 16.9 18.5 18.2 14.8  9.9  3.4  0.6  8.4  144
1842 -4.6 -1.5  2.8  6.5 13.3 16.8 18.3 19.2 13.8  7.2  1.9  0.6  7.9  142
1843 -0.6  1.0  1.9  7.4 11.6 16.1 18.1 18.1 14.1  8.7  3.3  0.9  8.4  139
1844 -2.8 -2.6  1.2  7.9 13.2 16.7 17.8 17.0 14.5  8.9  2.8 -3.6  7.6  142
1845 -1.0 -4.9 -1.0  7.8 11.6 17.5 19.5 17.4 13.9  8.8  4.6 -0.0  7.9  145
1846 -1.2  0.2  4.5  8.3 13.0 18.1 20.2 20.0 15.1  9.9  2.7 -2.5  9.0  139
1847 -3.8 -1.7  1.0  6.6 13.8 16.5 19.5 19.4 14.2  8.7  4.2 -1.6  8.1  143
1848 -7.1  0.5  3.4  9.5 13.5 17.8 19.1 17.9 13.8  9.5  3.0 -1.0  8.3  151
1849 -2.8  0.7  2.5  6.9 13.2 17.2 18.8 17.8 13.9  9.5  4.0 -2.0  8.3  153
1850 -5.8  0.9  1.2  7.8 12.6 17.6 19.2 18.6 13.6  7.8  4.2  0.5  8.2  153
1851 -0.7 -0.6  2.4  8.3 12.1 17.0 18.5 18.4 14.3 10.3  3.2  0.5  8.6  169
1852 -0.1 -0.4  2.0  6.3 13.5 17.1 19.8 18.5 14.7  8.9  5.1  2.9  9.0  174
1853  1.0 -1.1  1.1  7.2 13.1 17.4 19.8 18.7 14.5 10.3  4.0 -1.6  8.7  178
1854 -1.7 -0.4  3.7  8.2 13.9 16.7 19.9 18.6 14.8 10.4  3.3  2.0  9.1  177
1855 -2.4 -3.0  2.6  8.4 13.1 17.4 19.5 19.0 14.6 11.1  3.9 -2.3  8.5  181
1856  0.6  0.9  2.1  8.7 12.6 17.5 18.6 18.5 14.2  9.9  2.4  1.4  8.9  196
1857 -1.1  0.2  3.6  8.0 13.0 17.1 19.4 19.3 15.2 11.0  4.6  2.7  9.4  197
1858 -1.1 -1.4  3.1  8.7 12.9 18.4 18.9 18.2 15.7 10.6  2.4  1.6  9.0  197
1859  1.0  2.5  5.5  8.8 13.7 17.5 20.3 19.3 14.7 10.6  4.9  0.2  9.9  202
1860  1.1 -0.7  2.3  7.9 13.4 16.8 17.9 17.7 14.6  9.8  3.7 -0.6  8.7  195
1861 -3.0  2.4  5.2  7.4 12.0 17.4 19.0 18.8 14.5 10.5  5.0  1.6  9.2  198
1862 -1.1 -0.1  4.7  8.9 13.6 15.9 17.7 16.9 14.3 10.1  3.5  0.2  8.7  199
1863  2.2  2.2  4.4  8.6 13.0 16.3 17.4 18.0 14.0 10.3  5.4  2.2  9.5  197
1864 -1.7  1.0  4.9  8.1 12.1 16.7 18.0 16.7 14.1  8.7  3.6 -0.1  8.5  212
1865  1.5 -0.7  2.2  9.8 14.4 16.0 19.5 17.5 15.7 10.3  6.6  2.4  9.6  218
1866  3.3  2.9  4.4  9.7 12.1 17.5 18.4 17.4 15.5  9.9  5.8  3.2 10.0  245
1867  0.8  4.0  3.4  9.0 12.0 16.3 17.6 17.9 14.9 10.3  5.5  1.2  9.4  243
1868  0.7  2.7  5.5  8.8 14.8 17.2 19.3 18.8 15.4 10.6  5.4  4.6 10.3  245
1869  2.5  5.4  4.5 10.1 13.4 15.9 18.8 17.9 15.6 10.3  6.3  2.9 10.3  234
1870  2.3  0.9  4.6  9.6 13.9 17.1 19.3 17.6 14.9 10.7  6.8  0.9  9.9  243
1871  0.2  1.6  6.7  9.7 12.7 15.9 18.9 18.8 14.9 10.6  5.2  1.2  9.7  274
1872  2.5  2.9  5.4 10.3 14.1 17.4 19.5 18.6 15.7 11.4  6.9  2.9 10.6  297
1873  2.4  1.9  5.4  8.7 12.9 17.5 19.6 19.1 15.1 11.1  6.0  3.8 10.3  314
1874  3.2  2.8  5.3  9.6 13.0 17.2 19.5 18.2 16.1 11.8  6.2  2.5 10.4  325
1875  1.0  0.5  4.0  9.0 14.5 17.8 19.0 19.0 15.5 10.6  5.6  2.3  9.9  340
1876  2.7  3.9  6.2 10.6 13.4 18.1 20.0 19.4 15.9 12.1  6.7  3.1 11.0  343
1877  2.9  4.8  5.6 10.0 13.5 18.1 19.6 19.3 15.7 11.6  8.6  5.5 11.3  365
1878  3.5  5.6  8.2 12.3 15.0 18.1 20.0 19.8 17.3 13.3  8.1  3.6 12.1  403
1879  2.4  3.6  6.6 10.3 14.4 17.7 19.3 19.5 16.4 13.1  7.2  2.4 11.1  419
1880  3.8  4.7  7.1 11.2 15.1 17.9 19.9 19.6 17.1 12.1  7.2  4.4 11.7  426
1881  1.4  3.5  6.8 10.4 15.4 17.5 20.2 19.6 16.9 11.7  7.9  5.2 11.4  468
1882  4.1  5.1  7.8 10.8 14.5 17.7 19.6 19.5 16.6 12.6  7.3  3.3 11.6  492
1883  1.7  3.2  4.9 10.4 14.5 18.3 19.6 19.1 16.2 12.0  7.7  3.8 11.0  505
1884  2.2  3.7  6.2  9.9 14.3 17.5 19.4 19.2 16.6 11.9  6.6  3.2 10.9  515
1885  0.6  2.6  5.2 10.1 13.8 17.4 19.6 18.4 15.9 11.4  7.3  3.9 10.5  527
1886  1.1  1.9  5.5 11.0 14.6 17.5 19.7 19.4 16.7 12.3  7.2  2.9 10.8  555
1887  1.2  2.3  5.6 10.1 14.9 18.0 20.4 19.0 16.3 11.1  7.2  3.0 10.8  576
1888  1.0  2.2  4.9 10.4 14.4 17.9 19.5 19.0 16.4 11.7  7.5  4.1 10.7  599
1889  2.2  2.4  6.3 11.0 15.5 18.3 19.8 19.3 16.1 12.0  7.5  4.2 11.2  630
1890  3.1  3.4  6.4 11.0 14.7 18.2 19.8 19.5 16.7 12.1  7.6  2.8 11.3  652
1891  1.3  2.3  5.8 10.5 14.7 18.0 19.8 19.4 17.2 12.5  6.8  4.8 11.1  691
1892  1.6  3.7  5.7 10.5 14.6 18.4 20.0 20.0 17.2 12.4  7.0  2.2 11.1  722
1893 -0.7  1.6  6.2 10.5 14.7 18.4 20.3 19.9 16.6 12.8  7.1  3.7 10.9  743
1894  1.9  3.1  7.3 11.5 14.8 18.4 20.5 19.8 16.4 12.4  7.4  3.9 11.5  763
1895 -0.4 -0.3  5.4 11.8 15.8 19.5 20.8 20.9 18.3 11.6  6.8  2.7 11.1 1397
1896  1.1  2.8  4.9 11.6 16.6 19.8 21.7 21.0 17.0 12.0  6.0  3.2 11.5 1453
1897  0.5  2.7  5.8 11.3 15.8 19.5 22.0 20.9 18.6 13.3  6.7  2.0 11.6 1547
1898  2.4  2.9  6.4 10.8 15.8 19.9 21.7 21.5 18.4 12.2  6.4  2.2 11.7 1594
1899  1.3 -0.0  4.8 11.3 15.8 19.6 21.6 21.3 17.7 13.3  8.7  2.4 11.5 1632
1900  2.2  1.4  5.4 11.5 16.1 19.9 21.6 21.9 18.3 14.4  7.3  3.6 11.9 1674
1901  1.7  1.0  6.5 11.2 16.0 19.8 22.8 21.5 17.6 13.4  6.9  2.4 11.7 1696
1902  1.9  2.0  7.4 11.2 16.2 19.0 21.2 20.6 17.1 13.0  8.3  2.0 11.7 1747
1903  2.0  2.4  7.8 11.2 15.8 18.3 20.9 20.3 17.2 12.9  6.7  1.9 11.5 1808
1904  0.3  1.5  6.3 10.7 15.9 19.1 20.9 20.4 17.7 13.0  7.9  2.8 11.4 1849
1905  0.3  0.4  8.0 11.3 15.8 19.5 21.3 21.1 18.2 12.2  7.9  3.5 11.6 1891
1906  3.4  3.0  5.1 12.6 16.0 19.4 21.4 21.3 18.5 12.9  7.4  3.8 12.1 1934
1907  2.6  3.5  8.5 10.1 14.3 18.3 20.9 20.3 17.7 13.2  7.8  4.5 11.8 2066
1908  3.4  3.5  7.7 12.1 15.7 18.8 21.1 20.3 18.1 12.7  8.2  4.1 12.2 2088
1909  2.6  3.9  6.8 10.8 15.0 19.2 20.6 21.0 17.6 12.8  9.1  1.7 11.8 2134
1910  2.7  2.5 10.0 12.7 15.3 19.0 21.2 20.3 17.9 13.7  7.3  3.2 12.2 2176
1911  2.8  3.7  7.8 11.3 16.5 19.8 21.1 20.5 18.2 12.9  6.9  4.4 12.1 2227
1912  0.2  3.2  5.7 11.8 16.0 18.7 20.7 19.8 16.9 12.8  8.1  4.4 11.5 2255
1913  3.0  2.6  6.7 12.2 15.4 18.9 20.9 21.0 17.3 12.6  9.3  4.9 12.1 2323
1914  4.0  2.5  7.3 11.7 16.2 19.4 21.3 20.6 17.5 13.8  8.4  2.2 12.1 2379
1915  2.0  4.9  5.8 13.1 14.9 18.2 20.3 19.8 17.5 13.4  8.2  3.7 11.8 2395
1916  1.8  3.0  6.5 11.2 15.2 17.9 21.3 20.5 17.0 12.3  7.3  2.0 11.3 2406
1917  1.3  1.4  5.9 10.4 13.5 18.2 21.1 20.0 17.1 11.3  8.0  1.1 10.8 2426
1918 -0.4  3.1  8.2 10.8 15.7 19.1 20.3 20.7 16.4 13.7  7.7  4.5 11.6 2451
1919  3.2  3.2  6.8 11.6 15.3 19.3 21.1 20.4 17.9 12.6  6.8  2.1 11.7 2450
1920  1.5  3.6  7.1 10.1 15.1 18.6 20.6 20.1 17.8 13.4  7.2  3.8 11.6 2463
1921  4.0  4.8  9.0 12.1 15.9 19.8 21.7 20.3 18.2 13.4  7.6  4.3 12.6 2528
1922  1.2  3.0  7.1 11.7 16.1 19.5 20.6 20.6 18.2 13.3  8.1  3.5 11.9 2553
1923  3.4  2.1  6.1 11.0 15.2 18.9 20.9 20.1 17.6 12.5  8.3  5.3 11.8 2592
1924  0.9  3.7  6.0 11.1 14.7 18.7 20.5 20.5 16.9 13.6  7.9  1.7 11.3 2628
1925  1.7  4.9  7.8 12.7 15.3 19.4 20.9 20.4 18.0 11.1  7.5  3.8 12.0 2666
1926  2.8  5.1  6.7 11.1 15.7 18.5 20.9 20.6 17.3 13.1  7.4  2.9 11.8 2717
1927  2.4  4.6  7.6 11.5 15.1 18.4 20.8 19.7 17.7 13.8  8.3  1.9 11.8 2716
1928  2.9  3.9  7.3 10.6 15.8 18.0 21.1 20.6 17.1 13.3  8.1  4.1 11.9 2726
1929  0.5  0.9  7.8 11.3 15.0 18.5 20.9 20.6 17.2 13.1  7.1  3.5 11.4 2762
1930  0.3  5.3  7.1 12.4 15.5 19.1 21.6 21.0 17.9 12.4  7.9  3.6 12.0 2787
1931  3.7  5.1  7.0 11.8 15.5 19.7 21.7 20.6 18.6 14.1  9.0  5.2 12.7 2883
1932  4.2  4.5  5.9 11.9 15.9 19.2 21.0 20.9 17.8 12.9  7.6  3.4 12.1 2919
1933  3.9  2.9  7.3 11.5 15.8 19.9 21.4 20.5 18.4 13.3  7.9  3.9 12.2 2953
1934  4.0  3.7  7.4 12.3 17.1 19.7 21.8 20.8 17.4 13.7  9.2  4.0 12.6 2973
1935  2.2  4.9  8.0 11.1 14.7 18.6 21.5 20.8 17.5 13.2  7.3  3.1 11.9 2988
1936  1.2  0.3  7.7 11.0 16.5 19.4 22.0 21.2 18.0 12.9  7.4  4.3 11.8 3051
1937  1.1  3.2  6.2 11.3 16.1 19.2 21.4 21.4 17.8 13.1  7.6  3.2 11.8 3082
1938  2.7  4.1  8.7 12.2 15.7 19.0 21.1 21.1 18.2 14.1  7.8  3.8 12.4 3111
1939  3.5  2.8  7.0 11.5 16.3 19.0 21.2 20.7 18.0 12.9  8.0  5.4 12.2 3147
1940 -0.0  3.5  7.0 11.2 15.6 19.1 21.1 20.4 17.8 13.6  7.2  4.7 11.8 3181
1941  2.8  3.9  6.8 12.5 16.2 19.0 21.2 20.3 17.5 13.7  8.6  5.0 12.3 3282
1942  2.7  3.0  7.8 12.4 15.6 18.9 20.9 20.3 17.4 13.5  8.3  3.6 12.0 3290
1943  1.7  4.7  6.5 11.9 15.5 18.9 21.0 20.5 17.4 13.4  7.8  4.2 12.0 3329
1944  3.8  4.2  6.5 11.1 16.2 18.9 20.6 20.4 17.8 13.5  8.2  3.0 12.0 3334
1945  2.0  3.9  8.8 11.7 14.7 18.2 20.3 20.5 17.5 13.1  7.9  2.7 11.8 3380
1946  3.2  4.4  9.0 12.7 15.2 18.6 20.8 20.0 17.5 13.1  8.2  4.3 12.2 3436
1947  3.1  3.0  6.9 11.7 15.5 18.4 20.6 21.0 17.9 14.5  7.4  4.0 12.0 3497
1948  2.3  3.4  6.7 12.3 15.8 19.1 20.7 20.4 17.9 13.0  8.5  4.1 12.0 3658
1949  2.6  3.8  7.4 12.2 16.2 19.2 21.1 20.7 17.4 13.7  9.2  4.4 12.3 3950
1950  2.7  4.4  7.1 11.3 15.9 19.0 20.5 20.0 17.5 14.1  7.8  4.2 12.0 4036
1951  4.1  5.5  8.1 12.6 16.7 19.1 21.2 20.9 18.2 14.2  8.8  5.7 12.9 4709
1952  5.1  6.3  8.1 13.4 16.6 20.0 21.6 21.1 18.5 13.8  9.2  5.9 13.3 4872
1953  5.6  6.4  9.7 12.8 16.7 20.0 21.5 21.1 18.6 15.0 10.0  6.6 13.7 4971
1954  3.9  7.0  8.6 13.3 16.1 19.7 21.4 20.9 18.7 14.5 10.3  6.1 13.4 5066
1955  4.8  5.7  8.5 13.4 16.8 19.3 21.6 21.4 18.5 14.6  8.6  5.3 13.2 5058
1956  4.5  4.9  8.5 12.6 16.6 19.6 20.9 20.5 18.0 14.5  8.9  6.1 13.0 5104
1957  3.4  6.1  8.8 13.0 16.5 19.8 21.4 20.8 18.1 13.7  9.5  6.7 13.2 5100
1958  4.8  5.2  8.2 13.0 17.2 19.4 21.3 21.0 18.3 14.2  9.7  5.3 13.1 5123
1959  3.8  5.3  9.2 13.2 16.8 19.9 21.6 21.2 18.2 13.9  8.5  6.2 13.1 5166
1960  4.3  5.7  7.5 13.1 16.4 19.7 21.2 20.9 18.5 14.5  9.7  5.4 13.1 5250
1961  4.2  6.6  9.7 12.9 16.5 19.9 21.3 21.1 18.4 14.4  9.6  5.2 13.3 5468
1962  4.1  6.0  8.3 13.2 17.0 19.4 20.9 20.9 18.1 14.8  9.9  5.8 13.2 5584
1963  3.0  5.5  9.2 13.2 16.8 19.7 21.4 20.9 18.6 15.5 10.4  4.6 13.2 5681
1964  4.7  5.1  8.4 13.2 17.0 19.5 21.4 20.4 18.0 14.0  9.6  5.2 13.0 5718
1965  4.8  5.4  8.0 12.8 16.7 19.2 20.7 20.4 17.7 14.4  9.9  6.6 13.0 5875
1966  3.9  6.1  9.6 12.8 16.3 19.4 21.3 20.5 18.0 14.2  9.9  5.8 13.2 5937
1967  5.0  5.4  9.3 12.9 16.2 19.2 20.8 20.6 18.0 14.6  9.5  5.8 13.1 5947
1968  4.0  5.4  9.9 13.3 16.1 19.2 20.8 20.2 18.0 14.4  9.8  5.4 13.0 5962
1969  3.9  5.4  8.2 13.3 16.9 19.0 21.0 20.8 18.1 13.9  9.9  6.1 13.0 5993
1970  3.8  6.4  8.4 13.1 16.6 19.5 21.1 20.8 18.0 14.1  9.6  5.8 13.1 6001
1971  4.3  5.9  8.5 12.7 16.1 19.2 20.6 20.5 18.0 14.4  9.6  6.1 13.0 5890
1972  4.1  5.2  9.4 12.9 16.6 19.1 20.6 20.5 17.7 13.7  9.2  5.6 12.9 5887
1973  5.0  6.4 10.1 13.0 16.5 19.4 21.1 20.8 18.1 14.5  9.2  5.9 13.3 5944
1974  4.4  5.8  9.4 13.1 16.2 19.0 20.8 20.2 17.3 13.8  9.6  6.0 13.0 5948
1975  5.1  5.6  8.6 12.4 16.6 19.1 21.1 20.4 18.0 14.2  9.7  5.5 13.0 5968
1976  4.0  6.4  8.5 12.9 15.9 18.9 20.4 19.9 17.5 13.0  8.4  4.9 12.6 5820
1977  2.6  6.4  9.8 13.5 16.8 19.3 21.0 20.4 18.0 14.1  9.9  5.5 13.1 5795
1978  3.7  4.7  9.0 12.8 16.3 19.1 20.8 20.2 18.0 14.0  9.2  5.3 12.8 5797
1979  3.2  4.4  9.3 12.4 16.0 19.2 20.7 20.4 18.1 14.3  9.4  6.8 12.8 5746
1980  4.1  5.2  8.3 12.9 16.5 19.2 21.1 20.6 18.0 13.8  9.9  5.5 12.9 5724
1981  4.5  6.3  9.5 13.4 15.8 19.1 20.8 20.3 17.7 13.4  9.3  5.7 13.0 5532
1982  2.6  4.6  8.2 11.8 16.3 18.3 20.4 20.1 17.6 13.7  8.8  6.2 12.4 5354
1983  4.7  5.9  9.0 12.2 15.8 18.6 20.8 20.9 18.0 13.9  9.4  3.8 12.7 5320
1984  3.8  6.1  7.9 12.1 15.8 18.8 20.4 20.4 17.0 13.7  8.7  4.8 12.5 5251
1985  2.8  4.2  8.6 13.1 16.5 18.4 20.5 20.1 17.1 13.5  8.0  3.8 12.2 5193
1986  4.5  4.7  9.1 12.9 16.3 19.2 20.5 20.1 17.4 13.3  8.0  5.1 12.6 5136
1987  3.6  5.8  7.8 12.8 16.5 19.5 21.2 20.4 18.1 13.3  9.1  5.6 12.8 5045
1988  3.3  4.4  8.2 12.5 16.5 19.6 21.5 21.1 17.8 13.3  8.6  4.8 12.6 4998
1989  4.2  4.0  8.3 12.9 16.2 19.0 21.1 20.5 17.7 13.6  8.4  3.5 12.4 4926
1990  5.6  6.7 10.4 13.3 16.6 20.0 21.6 21.5 19.1 15.0 11.5  6.9 14.0 4701
1991  6.6  8.9 11.3 14.4 17.5 19.9 21.1 20.9 18.5 15.1  9.9  7.6 14.3 3743
1992  7.3  8.9 11.1 14.0 17.1 19.1 20.5 20.2 18.1 14.4  9.2  5.6 13.8 3683
1993  4.6  4.9  9.0 13.2 17.3 19.9 21.8 21.5 18.2 14.2  8.4  6.3 13.3 3283
1994  4.4  5.3 10.2 14.1 17.2 20.9 22.2 21.6 19.1 14.9 10.5  7.3 14.0 3250
1995  5.7  6.9 10.3 13.2 17.0 20.2 22.4 22.4 18.7 15.1  9.6  6.0 14.0 3161
1996  4.9  6.5  8.7 13.1 17.4 20.5 22.0 21.6 18.3 14.4  9.0  6.6 13.6 3226
1997  4.6  7.2 10.3 12.7 16.9 20.3 21.9 21.5 19.1 14.7  9.7  6.6 13.8 3182
1998  6.3  8.4  9.8 14.1 18.1 20.5 22.5 22.2 20.0 15.1 10.5  7.0 14.5 3165
1999  5.7  7.8  9.7 13.9 17.3 20.4 22.5 21.8 18.8 14.7 11.1  6.9 14.2 3173
2000  5.2  7.6 10.7 13.9 17.8 20.4 21.8 22.0 18.8 14.7  8.6  4.5 13.8 3151
2001  3.8  4.9  8.8 13.4 17.3 20.3 22.1 22.3 18.6 14.7 10.8  5.8 13.6 2924
2002  5.3  6.4  8.8 13.6 16.6 20.9 22.9 21.9 19.5 13.6  9.4  5.7 13.7 2960
2003  4.3  4.7  9.1 13.2 17.2 20.3 22.4 22.4 18.7 14.8  9.6  6.0 13.6 2941
2004  3.5  5.7 10.5 13.6 17.4 20.1 21.9 21.1 18.9 14.6  9.7  5.6 13.5 2966
2005  4.8  5.9  8.7 13.7 16.8 20.7 22.6 21.9 19.5 14.6 10.0  4.8 13.7 2814
2006  5.3  5.5  8.9 14.0 17.2 20.6 22.9 21.7 18.4 14.1  9.9  6.4 13.7 2793
2007  5.0  4.9 10.2 13.1 17.6 20.7 22.2 22.3 19.3 15.2  9.3  5.7 13.8 2784
2008  3.9  5.3  9.3 13.2 16.8 20.5 22.3 21.6 18.8 14.4  9.7  5.1 13.4 2774
2009  4.1  6.6  9.4 13.5 17.5 20.3 21.7 21.6 19.0 13.8 10.7  5.1 13.6 2702
2010  4.4  5.2 10.0 14.1 17.4 20.9 22.6 22.2 19.2 15.1 10.0  5.2 13.9 2708
2011  4.0  5.8  9.4 13.8 17.0 20.5 22.5 22.0 19.1 14.5  9.8  6.1 13.7 2682
2012  5.4  6.0 11.1 14.1-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0  9.1 2528
AA    3.5  4.8  8.2 12.4 16.2 19.2 21.1 20.7 17.9 13.7  8.8  4.8 12.6
Ad    0.7  2.1  5.2  9.8 14.2 17.7 19.5 19.0 15.8 11.0  5.9  2.3 10.3
 
For Country Code ALL
 
From input file ./data/v3.mean

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About E.M.Smith

A technical managerial sort interested in things from Stonehenge to computer science. My present "hot buttons' are the mythology of Climate Change and ancient metrology; but things change...
This entry was posted in AGW and GIStemp Issues, NCDC - GHCN Issues and tagged , , , , . Bookmark the permalink.

10 Responses to GHCN v1 v2 v3 All Data

  1. Thanks for this.

    I’d seen month-by-month average temps and noted the more pleasant winter and more pleasant summer effects. Australia, for example, showed this. I cannot bring myself to tremble in fear over this prospect.

    On that interesting graph: I suspect that the three-year add in V3 will be a source of nitpicking. Can you constrain the same date ranges for each and see what it looks like?

    ===|==============/ Keith DeHavelle

  2. pouncer says:

    This will take some time to think about.

    A thought. Steven Mosher is leaning warmist, having done his own analysis and losing patience with those of us less willing to do the exercise ourselves. Which is fine, the science is better, as is justice generally, when sharp advocates argue on both (or all) sides of a dispute. What each would prefer to overlook is exposed by the other and perhaps a layman — as a juror — might recognize a situation than neither advocate would admit.

    Another analogy, though, are traders working both sides in a developing market. One willing buyer believes a number is headed up, and soon. A willing seller believes that number is either stable, or headed down. A trade is made. Or, sometimes a hedge.

    Mosher recently has taken to arguing that the various temperature reports are NOT the “T” that is raised to the fourth power in the black body radiation equation. Instead, it is, he says, an index. A proxy, actually. An indicator of temperature, in much the way a sample of 30 company’s stock prices in the Dow Jones Industrial Index are a proxy for the entire S&P 500, or Wiltshire 3000 or US government calculated GDP or whatever else one might use to track the ups and downs of overall “wealth”. We might have quite legitimate quibbles about which companies are in, or out, of the Dow this decade versus last. We might dispute whether the price needs to be adjusted for inflation or commodity pricing or hedonic values. But overall the Dow does seem to track the health and wealth of the market generally, (we think) even though companies come and go and currencies change and the times and volumes of trades change from eighths to tenths and so on and so forth.

    I’d like to pick his brain about that notion. But I’d also like to hear from somebody who REALLY understands the notions of financial indexes.

    Uhm. Who do I know who makes something of a living understanding financial indexes, AND has a serious hobbyist’s interest in global temperatures?

    Another thought. Mao killed a potload of people because he confused the lines on a chart he supposed to represent steel-production with the actual production of steel, and mistakenly believed that steel was a causal factor in market power rather than a measure of it. Proxies, indexes, and causes are different. Or so I think.

  3. omanuel says:

    Thanks, E.M., for the information.

    While I agree the science is better, as is justice generally, when sharp advocates argue on both (or all) sides of a dispute, my own experiences suggest that:

    Deception in global temperature data is only a minor, but glaring, example of the pervasive dishonesty that has destroyed the ability of world leaders to formulate policies in the best interest of society.

    World leaders do not understand science, and shouldn’t be expected to.

    I see social and economic collapse ahead if skeptics cannot quickly find a way to restore integrity to government science.

    In this regard, Steve Mosher would be interesting study, if there were not far more important issues at hand.

    With kind regards,
    Oliver K. Manuel
    Former NASA Principal
    Investigator for Apollo
    http://www.omatumr.com

  4. George says:

    From Tom Peterson (NOAA) to Phil Jones 4992.txt

    NASA was blameless as they just use GHCN. GHCN has been in serious need of maintenance and improvements (e.g., to incorporate all the CLIMAT messages, to account for changing station numbers, etc.) for quite some time. But instead of spending time and energy improving GHCN version 2, the plan was to create GHCN version 3 instead. Unfortunately, GHCN version 3 has taken longer than anticipated.
    Regards,
    Tom

    4798.txt also discusses GHCNv2 being somewhat useless because of the drop in number of stations.

    Just grepping in GHCN through the climategate2 emails yields what looks like a lot of complaints and frustrations with it among the scientists. Seems nobody had much use for v2

  5. omanuel says:

    Crooked scientists advising crooked politicians how to win more votes from crooked capitalists, communists, liberals, conservatives, environmentalist, etc. The root of the problem: Naked apes are highly manipulative, creative, intelligent and inquisitive.

    All religions caution mankind of the inherent dangers that accompany our talents.

  6. Pascvaks says:

    G.I.G.O.?
    _____________________

    There appears to be something very healthy and beneficial in the practice of having great minds work in Patent Offices, or some such, and slaving away in universities and wearing the same shirt 3 times a week. I think we’d be much more advanced, and advancing more too, if we did not sponsor mediocrity with government jobs, grants, or research awards –there appears to be something in the numbers that would indicate that it is very counterproductive to spend tax money on such things, and hire people to manage the tax money spent by people doing such things, and account for the money for such things, and write reports quarterly and annual reports to Congress on the money spent for such things, and lobby for more money each year to build a new ‘green’ building and buy new ‘green’ computers to manage such things for the people of the United States of America. You know fellow fools, I think we’re being milked

  7. Gary says:

    As one of Anthony Watts’ SurfaceStations surveyors I’ve interviewed a few station managers. One in particular told me that in addition to the temps taken in the Stevenson screen (5 foot level), they also took unofficial ones at ground level and often found these 2-3 degrees colder at the morning reading after the cool air had settled. The station is sited at the bottom of a hill in a field where agricultural trials have been conducted for decades. This points out a concern for trying to use the “official” datasets for climatology — microsite effects are likely to be all over the map and to change with time even if the station doesn’t move. Maybe it doesn’t make much difference to a global average when everything is homogenized, but it certainly expands the confidence intervals. Parsing down to tenths and hundredths of a degree is going beyond what the data support.

  8. E.M.Smith says:

    @Keith DeHavelle:

    Yes, it is on my “to do” list to do all the comparisons with “the same years”. First, though, I wanted to get the dT/dt anomaly code done (and it is now – just pending QA combing) and yes, those reports, too, need a version comparing like years.

    But having been up to the wee hours last night chasing bogus data and doubling the size of the project (as I now need to A/B the qca and qcu versions…)

    https://chiefio.wordpress.com/2012/05/24/ghcn-v3-a-question-of-quality/

    I’m likely to be playing “recover and catch up” for a day or two ;-)

    Seems that there were a load of comments come in over the last 24 hours and I’m behind on reading my own blog…

    FWIW, part of the “moderation of seasons” may simply be more coverage in the Southern Hemisphere; so also on the “to do” list is the same thing “by hemisphere”. Is the “seasonal moderation” the same when hemispheric effects are removed?

    Every time I find an interesting thing, it turns up a half dozen other interesting things to put on the “to do” list…

    @Pouncer:

    Stock indexes are imperfect. Some of them have imperfections that are an advantage.

    “Instrument change” in computing the Global Temperature is a horrible mistake and uncontrolled for quality of impact, near as I can tell. In stock indexes, who is in and who is out is tightly controlled and “for effect”.

    So the analogy is ‘reasonable’ in that both are indexes, but seriously flawed in that the fundamental “issue” is strongly addressed in stock indexes and horridly mangled in thermometers. (One of the things that got me going on all this Global Warming stuff to begin with…)

    Take, for example, the S&P 500 Index. It has a strong growth bias built in due to it being a “capital weighted index”. Only the 500 largest companies make it in. Companies that are going out of business automatically leave. Fast growing world changers rapidly enter. Great if your goal is growth of your portfolio. Not so good if you want to know “Is the total economy doing well?”.

    The “Dow 30 Industrials” was used in Dow Theory to compare to the Dow Transportation Index. The theory was the the time at which industrial production ramped up had a time offset from when goods were transported. But look at the “Dow 30” now. Drug companies. Banks. What happened to the “industrials” in it? So it is far less useful as a Dow Theory tool. (But the numbers have been kept rising even as the industrial capacity of the nation moved to Japan, Korea, and later China…)

    So, in short: HOW the index is constructed and managed is critical to it being usable and “suited to purpose”. IMHO the GAT calculated from the random gaggle of thermometers that constantly mutate over time is sorely unfit for purpose. Especially in the small weeds of 1/10 C precision that is needed to ‘discover’ any warming trend.

    Now, one other interesting parallel:

    BOTH have strong cycles. Look at the SPY for 20 years, you see a strong business cycle about the same as the sunspot cycle. (Loads of literature comments on that starting about Hershel and Jevons) and the folks who trade stock know and allow for the cyclical nature.

    The temperature series also has strong cyclicality in it (on several time scales) yet this is ignored by the GAT Keepers. They seem to exploit the cycles to get nice trend lines.

    In stock trading one of the classical novice errors is projecting trends out of cycles.

    So in the application of the “temperature index” I gross naivety at best (and negligence or fraud at worst).

    Hope that helps put it in perspective.

    @George:

    Interesting idea… “Use the email, Luke!” ;-)

    Yet more projects…

    FWIW v3 adds some stations,but it’s still way skewed.

    Per the “index” point above: IMHO it would be better if they just picked a small number of long lived well tended stations and made an “index” from them. But when I looked at long lived stations I found no warming… Gee, wonder why they didn’t choose them…

    @Pascvaks:

    Well, one of my “side ponderings” is trying to figure out where in the world one can go to escape it. Not found a great answer yet (though a couple of ‘good ones’ exist… some corners of Latin America at least let you disappear into a reality based local economy…)

    @Gary:

    The point about precision is one I’ve tried to raise several times (and often been beaten up about by academics who assert you can go to nearly any precision with averaging… when you can’t…)

    I’ve got a post or two up with a thermometer on a fence showing over 60 F and steam rising from the melting frost in the sun… or some such. The surface temperature field is fractal in form and the notion we can get ANY certain precision out of it a bit broken. I’ve used the story of a stream visited on a camping trip at about 18 years of age…

    It was a nice sunny day. Warm. About 70 F and closer to 80 F sitting in the sun. We got a bit hot and decided a dip in the “mountain stream” was just the ticket. Shucked off the shirt and jumped into the creek… shooting immediately out of the water onto a boulder in the middle… My friend declined my invitation to join me as “the water’s fine!”… something about my blinding translucent white skin having gone sort of bright pink… (The ‘flash headache’ ended after about 5 minutes on the rock in the sun). Seems that just around the bend, which we found upon further exploration, snow was melting ot make the stream…

    Yes, eventually I had to make the “plunge” to get back to shore. Decided to ‘ease in’ despite the longer immersion time to avoid the headache effect.

    So I like to ask: What is the REAL temperature of that meadow? The 32.x F creek / stream? The 32 F snow in patches of shade? The 70 F in the air in the shade? The 80 F near my skin in the sun? The 100 F of black rocks or tarmac in the sun? The 80 F above them?

    We assume that the air does a decent job of averaging those various points in the fractal temperature field and giving us a valid datum. The reality is that it knows nothing about the entropy change of snow to melt, or the specific heat of the water in the stream. It knows nothing about how the parking lot was repaved (or paved the first time) nor about how many trees are transpiring how much.

    Even the individual thermometer readings are only an “index” of the actual temperature field and can easily be 20 to 50 F “wrong” compared to particular parts of it.

    So what does an “index” made of averaging thousands of constantly variable and inconsistently present indexes mean?

    Not much, IMHO.

  9. E.M.Smith says:

    @Keith DeHavelle:

    The v3 results with 2010 onward zeroed has a couple of AA and Ad values that change in the 1/10 C range, but nothing that would make any real difference to the graphs IMHO. Just not significant.

    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
    --------------------------------------------------------------------------
    1701 -4.2 -1.5  1.6-99.0-99.0 15.4 18.9 15.8-99.0-99.0-99.0 -0.5  6.5    1
    1702  2.0 -0.5  0.6  2.6 10.9 16.0 16.0 15.8 10.1  7.5  0.2  0.6  6.8    1
    1703 -2.8 -0.9  0.6  7.7 14.1 16.1 15.4 16.3 11.4  6.1  2.2  2.5  7.4    1
    1704 -4.9 -0.5  3.9  9.4 11.8 14.1 17.1-99.0-99.0-99.0-99.0 -0.9  6.2    1
    1705 -7.1-99.0  1.0-99.0-99.0 16.0 18.3 17.8  8.7  7.5  0.7  1.8  7.2    1
    1706 -1.2 -1.0  2.8  7.4 12.8 17.2 16.6 15.6 11.8  8.5  3.5  2.5  8.0    2
    1707 -0.5  0.9  2.5  6.4 11.7 17.2 18.0 15.6 12.6  6.0  3.8  1.8  8.0    2
    1708  3.0  0.9  4.8  7.8 11.1 14.3 13.7 18.0 14.3  4.7  3.3 -1.6  7.9    2
    1709 -9.0 -3.9  0.9  9.4 11.7 16.7 16.0 16.0 12.2  8.1  5.6  2.0  7.2    2
    1710 -1.1 -0.2  4.2  6.9 12.9 15.2 15.2 16.5 13.8  9.4  7.4  6.5  8.9    2
    1711  3.5  0.0  4.7  9.5 12.2 16.9 16.0 15.6 13.3  9.3  6.5  1.5  9.1    1
    1712  0.2  2.9  4.1  7.7 12.3 16.3 16.8 14.9 13.1  9.5  5.0  4.2  8.9    1
    1713 -0.3  5.0  1.0  5.3 10.5 13.6 14.8 15.4 13.9  9.3  3.4  2.5  7.9    1
    1714  1.9  3.8  5.0  7.9 10.2 14.5 18.5 13.8 13.0  9.7  4.6  2.4  8.8    1
    1715  0.7  3.5  5.7  9.6 11.6 14.5 15.8 17.0 14.1 10.3  6.3 -1.5  9.0    1
    1716 -5.0  1.5  3.3  9.1 11.3 14.0 16.3 15.5 12.4  8.3  3.9  1.2  7.7    1
    1717  0.9  0.7  3.4  7.2 10.2 15.3 15.7 15.5 13.9  9.3  3.4  3.5  8.3    1
    1718 -1.6 -0.8  4.6  8.3 12.7 16.0 18.0 19.0 15.1  8.9  5.2  3.3  9.1    1
    1719  0.5  2.5  3.5  5.6 13.4 16.0 20.1 18.9 14.1  8.2  5.0  1.3  9.1    1
    1720  2.9  2.9  3.1  6.8 12.3 12.6 17.2 14.5 14.3  8.1  5.6  3.6  8.7    1
    1721  3.5  0.1  0.8  8.9 10.2 15.3 15.2 16.5 14.4  8.6  5.8  1.9  8.4    1
    1722  0.9  3.9  5.5  8.6 11.5 15.1 15.8 15.5 14.6 10.4  6.8  3.3  9.3    1
    1723  0.3  2.5  6.4  8.4 12.4 15.6 15.6 15.9 13.9 11.0  2.2  4.7  9.1    1
    1724  4.8  3.6  3.7  6.7 11.8 16.7 15.1 16.9 14.2  8.3  5.1  2.0  9.1    1
    1725  2.3  0.4  3.5  7.0 10.6 14.0 14.6 14.3 12.5  8.0  3.0  2.0  7.7    1
    1726 -1.8  0.2  2.5  7.8 14.1 16.2 15.6 14.4 14.2  9.2  5.3  0.1  8.1    1
    1727  2.6  3.6  3.7  7.0 15.0 15.4 16.8 17.5 14.7 11.5  3.6  2.5  9.5    1
    1728  2.5 -0.6  6.9  8.9 14.8 16.6 16.5 14.6 13.1  9.2  4.3 -0.6  8.9    2
    1729 -3.1  0.3  0.2  6.3 11.1 16.2 17.8 17.7 16.9 12.1  5.3  5.3  8.9    2
    1730  2.4  2.3  4.3  9.1 12.6 15.6 17.2 16.8 14.4  7.0  7.5  2.2  9.3    2
    1731 -0.5 -0.4  3.3  6.4 12.0 15.4 16.5 16.9 14.8 11.9  6.6  3.2  8.8    2
    1732 -0.6  3.3  5.3  9.8 12.9 14.2 16.1 16.2 14.1 10.4  4.4 -0.9  8.8    2
    1733  4.3  4.5  5.1 10.5 11.5 13.9 18.4 16.5 12.1  8.2  5.5  5.7  9.7    2
    1734  1.6  4.4  6.4  9.5 12.4 14.7 17.0 16.4 14.1  9.6  2.0  1.4  9.1    2
    1735  3.0  2.5  5.8  9.6 12.2 15.6 16.1 16.5 15.2  7.6  4.1  3.0  9.3    2
    1736  1.4  0.8  3.2  9.2 12.2 15.1 17.4 17.7 13.9  9.4  5.7  4.2  9.2    2
    1737  4.0  3.0  5.4  7.3 13.8 16.0 16.6 14.5 14.5  8.7  4.3  2.1  9.2    2
    1738  0.0  2.5  5.1  9.6 12.8 15.2 16.5 16.0 13.6  9.9  2.0  4.2  9.0    2
    1739 -1.4  1.0  3.6  5.2 12.3 14.9 17.7 15.0 13.8  5.8 -0.9  1.9  7.4    3
    1740 -6.4 -5.4  0.6  4.9  7.8 13.2 16.0 15.5 13.9  4.3  1.5  0.5  5.5    3
    1741 -2.6  2.3  2.5  5.4  9.4 13.8 17.1 15.8 12.9  9.7  5.8  1.4  7.8    3
    1742 -2.8  2.2  1.5  4.9  9.7 14.9 15.9 14.5 10.9  8.1  3.6 -2.5  6.7    3
    1743  1.2  1.8  2.6  4.9 12.4 18.0 17.8 17.0 14.4  4.4  4.6 -0.1  8.2    5
    1744 -3.8 -3.1  0.2  6.9 11.8 16.0 18.2 14.7 13.5  7.9  3.8 -1.4  7.1    5
    1745 -3.1 -3.7 -0.1  6.7 12.8 17.0 18.0 16.8 16.1  8.5  4.8 -0.3  7.8    5
    1746 -0.5 -0.4 -0.8  6.6 13.0 15.6 17.9 15.2 13.2  6.4  1.5  3.1  7.6    4
    1747 -1.5 -0.3 -0.5  7.2 11.2 18.5 18.2 15.8 15.2  9.5  4.4  1.0  8.2    4
    1748 -1.5 -1.5 -2.3  6.7 13.4 17.3 17.6 18.2 14.2  8.6  4.7  3.5  8.2    4
    1749 -0.1 -1.3  0.5  6.6 13.3 15.2 17.1 17.1 13.8  7.8  3.6  0.9  7.9    4
    1750 -0.5  1.4  4.4  7.3 12.1 15.7 19.1 17.6 13.6  6.2 -0.6 -0.9  8.0    5
    1751 -1.5 -3.5  3.5  6.4 12.8 16.0 17.9 17.4 12.2 11.1 -5.0-14.1  6.1    6
    1752 -5.8 -3.7  1.0  4.4  9.8 15.3 19.4 17.6 11.4  7.3  3.8 -0.9  6.6    5
    1753 -3.3 -1.7  3.5  7.0 11.7 16.5 18.3 17.0 13.7  9.4  2.4 -3.7  7.6    8
    1754 -2.6 -3.1 -0.6  6.5 12.6 16.5 17.3 17.1 13.1  9.2  3.5 -0.2  7.4    8
    1755 -5.3 -4.7  0.5  8.9 11.9 17.9 18.9 16.1 12.7  8.1  3.1 -0.0  7.3   10
    1756  0.2  1.6  2.4  5.5 10.5 17.7 18.9 16.3 14.0  8.1  0.9 -2.2  7.8   11
    1757 -3.7 -0.2  2.5  8.4 12.1 18.0 21.6 18.4 13.5  5.5  4.2 -1.6  8.2   13
    1758 -4.2 -1.2  2.8  7.0 13.8 17.3 17.5 18.0 12.5  6.7  4.2  0.1  7.9   13
    1759  1.0  2.3  3.9  8.1 12.2 17.7 20.4 18.8 14.7 10.0  2.2 -2.5  9.1   14
    1760 -3.8 -0.5  1.6  8.0 12.8 17.3 19.0 17.5 15.2  8.8  4.0  1.3  8.4   14
    1761 -1.7  1.0  5.2  7.4 13.7 18.1 19.0 18.9 15.2  6.8  3.6 -2.3  8.7   14
    1762  1.2  0.2  0.8 10.0 13.3 17.1 19.0 16.3 13.6  6.2  3.6 -1.2  8.3   13
    1763 -4.1  2.3  2.4  7.2 11.4 16.4 18.9 18.7 13.4  7.9  4.3  2.3  8.4   15
    1764  2.3  3.8  3.5  7.6 13.6 15.9 19.6 17.0 13.1  8.5  3.8  0.9  9.1   16
    1765  1.1 -1.4  5.3  8.6 12.0 16.4 17.3 18.1 13.9  9.7  4.4 -0.2  8.8   16
    1766 -3.0 -0.4  4.1  9.7 13.0 17.5 18.9 18.4 15.0  9.4  5.7 -0.2  9.0   16
    1767 -5.6  2.6  4.1  6.6 11.6 15.9 18.1 18.7 14.9  9.4  6.5 -0.9  8.5   17
    1768 -3.2  0.4  2.1  7.8 12.8 16.5 19.0 18.2 12.9  7.9  3.7  0.2  8.2   20
    1769 -0.8 -0.9  2.4  7.5 12.1 16.3 18.5 17.0 14.2  6.1  4.2  1.0  8.1   21
    1770 -1.3  0.9  0.5  6.8 12.8 16.3 18.4 18.7 15.6  9.4  4.1  1.8  8.7   21
    1771 -1.4 -1.6  0.8  5.1 14.6 17.3 18.7 17.5 14.4  9.9  3.2  2.2  8.4   22
    1772 -1.1  0.5  3.3  7.4 11.0 17.8 18.9 18.3 15.1 11.3  6.7  2.3  9.3   21
    1773  0.9 -0.5  3.6  8.7 14.1 16.6 18.6 18.8 15.3 10.9  4.7  2.5  9.5   23
    1774 -2.1  1.4  5.1  9.8 13.2 17.9 18.9 18.8 13.8  8.8 -0.1 -2.3  8.6   21
    1775 -1.5  2.3  4.2  7.2 12.2 18.2 19.8 19.4 15.7  9.5  3.0 -0.4  9.1   23
    1776 -8.0  0.3  3.1  7.0 10.3 17.2 19.5 18.2 13.2  8.4  3.0 -0.9  7.6   24
    1777 -3.5 -2.8  3.0  5.5 12.4 15.9 17.4 18.3 13.4  8.4  4.0 -1.9  7.5   25
    1778 -2.9 -1.7  2.1  8.8 13.4 16.3 20.3 18.6 12.6  6.6  3.2  1.0  8.2   24
    1779 -5.0  1.6  4.4  9.6 14.1 15.5 18.5 19.1 15.4 10.4  3.3  0.2  8.9   27
    1780 -5.4 -3.2  5.1  6.1 13.9 16.7 19.1 18.7 13.9  9.9  2.8 -1.7  8.0   28
    1781 -2.0  0.1  4.2  9.5 13.6 17.8 19.1 19.8 15.2  7.6  4.0 -0.8  9.0   32
    1782 -0.9 -4.2  1.2  6.4 11.7 17.4 19.3 17.8 14.1  7.3  0.8 -1.0  7.5   33
    1783 -0.8  2.0  1.8  8.4 13.8 17.5 20.1 18.4 14.8  9.6  3.2 -2.0  8.9   32
    1784 -4.8 -2.6  1.2  6.0 14.6 16.9 18.6 17.5 15.5  6.7  4.2 -1.6  7.7   33
    1785 -1.1 -2.6 -2.4  5.7 12.1 16.5 18.0 17.0 15.2  8.3  4.1 -0.7  7.5   34
    1786 -1.5 -0.6  1.0  9.0 12.2 17.4 17.3 17.1 13.3  6.8  0.6 -0.6  7.7   34
    1787 -1.7  1.5  4.7  7.0 11.9 17.6 18.1 18.3 14.4 10.7  3.8  1.7  9.0   31
    1788  0.1  0.4  3.0  9.0 14.0 18.2 20.9 17.6 15.7  8.6  2.4 -7.9  8.5   33
    1789 -3.2  1.3 -0.5  8.7 15.7 16.5 19.4 18.7 14.8  9.3  3.8  1.9  8.9   32
    1790  0.6  3.0  4.9  6.6 14.7 17.7 17.6 18.4 13.9  9.9  4.1  1.5  9.4   30
    1791  2.0  1.3  4.8 10.6 13.1 17.2 19.3 19.8 14.3  9.3  3.6  1.4  9.7   33
    1792 -1.3 -0.4  4.3  9.9 12.9 17.3 19.7 18.6 14.0  9.2  4.3  0.9  9.1   34
    1793 -1.9  2.5  4.0  7.4 12.8 16.4 20.7 19.3 14.2 11.1  5.1  2.0  9.5   33
    1794  0.2  3.3  6.6 11.6 13.9 17.9 21.1 17.8 13.4  9.4  5.0 -0.1 10.0   34
    1795 -6.2 -0.6  3.0 10.3 13.0 17.2 17.3 18.6 15.6 11.8  3.5  3.0  8.9   35
    1796  4.7  2.3  2.1  9.0 13.7 17.2 18.9 19.0 16.1  9.5  3.9 -2.0  9.5   37
    1797 -0.3  1.8  3.1  9.4 14.7 16.6 20.5 19.5 15.9 10.0  5.1  2.7  9.9   36
    1798  0.8  2.5  4.5  9.8 15.0 18.6 20.0 19.9 16.2 10.2  4.3 -1.8 10.0   39
    1799 -3.4 -0.9  2.7  7.5 12.5 16.5 18.6 18.5 14.9  9.9  5.3 -2.1  8.3   39
    1800  0.1  0.4  1.5 12.7 15.6 15.8 19.0 19.5 15.5 10.1  6.1  2.0  9.9   39
    1801  1.8  1.6  6.7  9.5 15.6 16.8 19.4 18.6 16.5 11.6  5.8  1.4 10.4   39
    1802 -2.0  1.3  5.2  9.9 12.9 17.9 18.5 20.6 15.6 12.3  5.2  1.8  9.9   39
    1803 -2.8 -1.2  3.8 11.2 12.7 17.1 20.5 19.9 13.6  9.6  4.9  1.1  9.2   41
    1804  2.4 -0.4  2.4  8.6 15.4 18.1 19.6 18.8 16.5 10.7  4.1 -1.3  9.6   41
    1805 -2.0 -0.1  3.6  7.4 12.3 16.0 18.5 18.1 15.5  7.0  2.1  0.9  8.3   42
    1806  1.8  2.4  3.9  6.9 15.2 16.9 18.5 18.6 15.9  9.8  6.1  4.4 10.0   46
    1807 -0.8  2.1  1.6  6.7 14.1 16.6 20.8 22.0 13.9 10.9  5.5  1.2  9.5   47
    1808 -0.5 -1.0 -0.2  6.2 15.1 17.0 20.6 19.6 15.4  8.5  4.1 -3.0  8.5   48
    1809 -3.0  1.9  2.5  5.3 14.2 17.0 18.8 18.9 14.6  8.9  2.8  2.4  8.7   49
    1810 -2.1 -0.8  3.9  7.3 12.5 16.0 18.7 18.4 16.1  9.4  4.3  1.7  8.8   49
    1811 -3.2  0.9  5.9  8.9 16.1 19.5 20.7 18.5 14.9 11.4  5.1  0.6  9.9   51
    1812 -3.7  0.3  1.8  5.1 13.0 16.6 17.9 18.3 13.3 10.0  2.0 -4.6  7.5   51
    1813 -3.6  1.8  3.3  9.5 14.1 16.1 19.2 17.6 14.5  9.2  4.5  0.7  8.9   56
    1814 -3.7 -3.6  1.9  9.8 11.3 16.1 19.9 18.1 13.3  8.5  4.7  1.8  8.2   54
    1815 -3.5  1.8  4.9  8.9 14.0 16.8 17.6 17.7 14.2 10.0  2.6 -1.7  8.6   54
    1816 -1.1 -2.8  2.2  7.8 12.0 15.8 17.6 16.7 14.0  9.1  3.2  0.2  7.9   59
    1817  1.1  2.4  3.3  5.7 13.1 17.7 18.5 18.0 15.1  6.7  4.7 -1.8  8.7   66
    1818 -0.1  0.1  4.0  8.7 12.8 17.6 19.5 17.0 14.5  9.6  5.3 -0.1  9.1   71
    1819  0.3  0.9  4.0  9.1 13.6 17.7 19.6 19.1 15.6  9.4  3.4 -1.4  9.3   71
    1820 -4.2  0.6  3.0 10.1 14.3 16.1 18.6 19.4 13.9  9.1  2.7 -1.1  8.5   77
    1821 -0.2 -0.8  3.4 10.3 13.2 14.9 17.4 18.1 15.4 10.1  5.8  2.4  9.2   81
    1822 -0.1  2.6  6.8  9.9 14.8 18.9 19.4 18.2 14.2 10.6  5.5 -1.5  9.9   77
    1823 -5.7 -0.3  3.7  7.2 13.8 16.6 18.1 18.9 14.7  9.6  3.4  1.0  8.4   85
    1824 -0.9  0.6  2.6  7.2 12.0 15.9 18.6 18.0 15.5  9.0  4.8  2.4  8.8   89
    1825  0.2 -0.2  1.9  9.0 13.5 17.2 18.9 18.3 15.3  9.4  5.4  2.7  9.3   95
    1826 -5.1  0.3  3.8  7.9 13.1 17.8 20.9 20.2 15.1 10.2  3.6  1.6  9.1   94
    1827 -2.5 -4.0  4.1  9.6 14.5 18.0 19.9 17.9 14.7 10.0  2.0  1.5  8.8   97
    1828 -2.4 -1.5  3.6  8.8 13.8 18.1 19.8 17.6 14.0  8.8  4.0  0.4  8.7  103
    1829 -4.9 -3.8  1.3  7.7 12.9 16.4 19.0 16.9 13.8  7.5  0.5 -5.6  6.8  111
    1830 -7.0 -3.8  3.1  8.7 12.9 16.6 19.1 17.8 13.0  8.1  4.6 -0.6  7.7  112
    1831 -4.7 -0.9  2.7  9.1 12.7 16.6 19.1 17.7 12.9 10.5  2.6 -0.7  8.1  117
    1832 -2.5 -0.8  2.3  7.4 11.6 16.0 17.3 17.8 12.7  8.7  1.9 -1.6  7.6  114
    1833 -4.1  1.1  1.6  6.8 15.0 17.8 17.7 15.5 13.3  8.5  3.6  1.3  8.2  115
    1834 -0.7 -0.6  3.0  6.8 14.6 17.4 20.7 19.5 15.2  8.8  3.3 -0.1  9.0  116
    1835 -0.6  0.9  3.0  6.9 12.2 16.7 19.0 17.0 13.8  8.2  0.5 -3.6  7.8  112
    1836 -2.9 -0.9  5.3  7.8 10.9 16.6 18.0 16.8 13.0  9.6  2.4  0.2  8.1  117
    1837 -2.5 -1.2  0.1  5.9 11.4 16.6 17.4 18.6 13.2  8.5  3.3 -1.4  7.5  123
    1838 -8.0 -4.6  1.7  5.9 12.6 16.3 18.4 16.8 14.5  7.9  2.5 -1.3  6.9  128
    1839 -2.9 -1.6 -0.9  5.0 13.0 17.6 19.7 17.8 14.5  9.2  3.2 -3.0  7.6  137
    1840 -2.4 -2.0  0.1  7.8 12.3 16.8 18.3 17.8 13.9  7.2  3.8 -5.0  7.4  141
    1841 -3.5 -3.8  2.8  8.1 14.9 16.9 18.5 18.2 14.8  9.9  3.4  0.6  8.4  144
    1842 -4.6 -1.5  2.8  6.5 13.3 16.8 18.3 19.2 13.8  7.2  1.9  0.6  7.9  142
    1843 -0.6  1.0  1.9  7.4 11.6 16.1 18.1 18.1 14.1  8.7  3.3  0.9  8.4  139
    1844 -2.8 -2.6  1.2  7.9 13.2 16.7 17.8 17.0 14.5  8.9  2.8 -3.6  7.6  142
    1845 -1.0 -4.9 -1.0  7.8 11.6 17.5 19.5 17.4 13.9  8.8  4.6 -0.0  7.9  145
    1846 -1.2  0.2  4.5  8.3 13.0 18.1 20.2 20.0 15.1  9.9  2.7 -2.5  9.0  139
    1847 -3.8 -1.7  1.0  6.6 13.8 16.5 19.5 19.4 14.2  8.7  4.2 -1.6  8.1  143
    1848 -7.1  0.5  3.4  9.5 13.5 17.8 19.1 17.9 13.8  9.5  3.0 -1.0  8.3  151
    1849 -2.8  0.7  2.5  6.9 13.2 17.2 18.8 17.8 13.9  9.5  4.0 -2.0  8.3  153
    1850 -5.8  0.9  1.2  7.8 12.6 17.6 19.2 18.6 13.6  7.8  4.2  0.5  8.2  153
    1851 -0.7 -0.6  2.4  8.3 12.1 17.0 18.5 18.4 14.3 10.3  3.2  0.5  8.6  169
    1852 -0.1 -0.4  2.0  6.3 13.5 17.1 19.8 18.5 14.7  8.9  5.1  2.9  9.0  174
    1853  1.0 -1.1  1.1  7.2 13.1 17.4 19.8 18.7 14.5 10.3  4.0 -1.6  8.7  178
    1854 -1.7 -0.4  3.7  8.2 13.9 16.7 19.9 18.6 14.8 10.4  3.3  2.0  9.1  177
    1855 -2.4 -3.0  2.6  8.4 13.1 17.4 19.5 19.0 14.6 11.1  3.9 -2.3  8.5  181
    1856  0.6  0.9  2.1  8.7 12.6 17.5 18.6 18.5 14.2  9.9  2.4  1.4  8.9  196
    1857 -1.1  0.2  3.6  8.0 13.0 17.1 19.4 19.3 15.2 11.0  4.6  2.7  9.4  197
    1858 -1.1 -1.4  3.1  8.7 12.9 18.4 18.9 18.2 15.7 10.6  2.4  1.6  9.0  197
    1859  1.0  2.5  5.5  8.8 13.7 17.5 20.3 19.3 14.7 10.6  4.9  0.2  9.9  202
    1860  1.1 -0.7  2.3  7.9 13.4 16.8 17.9 17.7 14.6  9.8  3.7 -0.6  8.7  195
    1861 -3.0  2.4  5.2  7.4 12.0 17.4 19.0 18.8 14.5 10.5  5.0  1.6  9.2  198
    1862 -1.1 -0.1  4.7  8.9 13.6 15.9 17.7 16.9 14.3 10.1  3.5  0.2  8.7  199
    1863  2.2  2.2  4.4  8.6 13.0 16.3 17.4 18.0 14.0 10.3  5.4  2.2  9.5  197
    1864 -1.7  1.0  4.9  8.1 12.1 16.7 18.0 16.7 14.1  8.7  3.6 -0.1  8.5  212
    1865  1.5 -0.7  2.2  9.8 14.4 16.0 19.5 17.5 15.7 10.3  6.6  2.4  9.6  218
    1866  3.3  2.9  4.4  9.7 12.1 17.5 18.4 17.4 15.5  9.9  5.8  3.2 10.0  245
    1867  0.8  4.0  3.4  9.0 12.0 16.3 17.6 17.9 14.9 10.3  5.5  1.2  9.4  243
    1868  0.7  2.7  5.5  8.8 14.8 17.2 19.3 18.8 15.4 10.6  5.4  4.6 10.3  245
    1869  2.5  5.4  4.5 10.1 13.4 15.9 18.8 17.9 15.6 10.3  6.3  2.9 10.3  234
    1870  2.3  0.9  4.6  9.6 13.9 17.1 19.3 17.6 14.9 10.7  6.8  0.9  9.9  243
    1871  0.2  1.6  6.7  9.7 12.7 15.9 18.9 18.8 14.9 10.6  5.2  1.2  9.7  274
    1872  2.5  2.9  5.4 10.3 14.1 17.4 19.5 18.6 15.7 11.4  6.9  2.9 10.6  297
    1873  2.4  1.9  5.4  8.7 12.9 17.5 19.6 19.1 15.1 11.1  6.0  3.8 10.3  314
    1874  3.2  2.8  5.3  9.6 13.0 17.2 19.5 18.2 16.1 11.8  6.2  2.5 10.4  325
    1875  1.0  0.5  4.0  9.0 14.5 17.8 19.0 19.0 15.5 10.6  5.6  2.3  9.9  340
    1876  2.7  3.9  6.2 10.6 13.4 18.1 20.0 19.4 15.9 12.1  6.7  3.1 11.0  343
    1877  2.9  4.8  5.6 10.0 13.5 18.1 19.6 19.3 15.7 11.6  8.6  5.5 11.3  365
    1878  3.5  5.6  8.2 12.3 15.0 18.1 20.0 19.8 17.3 13.3  8.1  3.6 12.1  403
    1879  2.4  3.6  6.6 10.3 14.4 17.7 19.3 19.5 16.4 13.1  7.2  2.4 11.1  419
    1880  3.8  4.7  7.1 11.2 15.1 17.9 19.9 19.6 17.1 12.1  7.2  4.4 11.7  426
    1881  1.4  3.5  6.8 10.4 15.4 17.5 20.2 19.6 16.9 11.7  7.9  5.2 11.4  468
    1882  4.1  5.1  7.8 10.8 14.5 17.7 19.6 19.5 16.6 12.6  7.3  3.3 11.6  492
    1883  1.7  3.2  4.9 10.4 14.5 18.3 19.6 19.1 16.2 12.0  7.7  3.8 11.0  505
    1884  2.2  3.7  6.2  9.9 14.3 17.5 19.4 19.2 16.6 11.9  6.6  3.2 10.9  515
    1885  0.6  2.6  5.2 10.1 13.8 17.4 19.6 18.4 15.9 11.4  7.3  3.9 10.5  527
    1886  1.1  1.9  5.5 11.0 14.6 17.5 19.7 19.4 16.7 12.3  7.2  2.9 10.8  555
    1887  1.2  2.3  5.6 10.1 14.9 18.0 20.4 19.0 16.3 11.1  7.2  3.0 10.8  576
    1888  1.0  2.2  4.9 10.4 14.4 17.9 19.5 19.0 16.4 11.7  7.5  4.1 10.7  599
    1889  2.2  2.4  6.3 11.0 15.5 18.3 19.8 19.3 16.1 12.0  7.5  4.2 11.2  630
    1890  3.1  3.4  6.4 11.0 14.7 18.2 19.8 19.5 16.7 12.1  7.6  2.8 11.3  652
    1891  1.3  2.3  5.8 10.5 14.7 18.0 19.8 19.4 17.2 12.5  6.8  4.8 11.1  691
    1892  1.6  3.7  5.7 10.5 14.6 18.4 20.0 20.0 17.2 12.4  7.0  2.2 11.1  722
    1893 -0.7  1.6  6.2 10.5 14.7 18.4 20.3 19.9 16.6 12.8  7.1  3.7 10.9  743
    1894  1.9  3.1  7.3 11.5 14.8 18.4 20.5 19.8 16.4 12.4  7.4  3.9 11.5  763
    1895 -0.4 -0.3  5.4 11.8 15.8 19.5 20.8 20.9 18.3 11.6  6.8  2.7 11.1 1397
    1896  1.1  2.8  4.9 11.6 16.6 19.8 21.7 21.0 17.0 12.0  6.0  3.2 11.5 1453
    1897  0.5  2.7  5.8 11.3 15.8 19.5 22.0 20.9 18.6 13.3  6.7  2.0 11.6 1547
    1898  2.4  2.9  6.4 10.8 15.8 19.9 21.7 21.5 18.4 12.2  6.4  2.2 11.7 1594
    1899  1.3 -0.0  4.8 11.3 15.8 19.6 21.6 21.3 17.7 13.3  8.7  2.4 11.5 1632
    1900  2.2  1.4  5.4 11.5 16.1 19.9 21.6 21.9 18.3 14.4  7.3  3.6 11.9 1674
    1901  1.7  1.0  6.5 11.2 16.0 19.8 22.8 21.5 17.6 13.4  6.9  2.4 11.7 1696
    1902  1.9  2.0  7.4 11.2 16.2 19.0 21.2 20.6 17.1 13.0  8.3  2.0 11.7 1747
    1903  2.0  2.4  7.8 11.2 15.8 18.3 20.9 20.3 17.2 12.9  6.7  1.9 11.5 1808
    1904  0.3  1.5  6.3 10.7 15.9 19.1 20.9 20.4 17.7 13.0  7.9  2.8 11.4 1849
    1905  0.3  0.4  8.0 11.3 15.8 19.5 21.3 21.1 18.2 12.2  7.9  3.5 11.6 1891
    1906  3.4  3.0  5.1 12.6 16.0 19.4 21.4 21.3 18.5 12.9  7.4  3.8 12.1 1934
    1907  2.6  3.5  8.5 10.1 14.3 18.3 20.9 20.3 17.7 13.2  7.8  4.5 11.8 2066
    1908  3.4  3.5  7.7 12.1 15.7 18.8 21.1 20.3 18.1 12.7  8.2  4.1 12.2 2088
    1909  2.6  3.9  6.8 10.8 15.0 19.2 20.6 21.0 17.6 12.8  9.1  1.7 11.8 2134
    1910  2.7  2.5 10.0 12.7 15.3 19.0 21.2 20.3 17.9 13.7  7.3  3.2 12.2 2176
    1911  2.8  3.7  7.8 11.3 16.5 19.8 21.1 20.5 18.2 12.9  6.9  4.4 12.1 2227
    1912  0.2  3.2  5.7 11.8 16.0 18.7 20.7 19.8 16.9 12.8  8.1  4.4 11.5 2255
    1913  3.0  2.6  6.7 12.2 15.4 18.9 20.9 21.0 17.3 12.6  9.3  4.9 12.1 2323
    1914  4.0  2.5  7.3 11.7 16.2 19.4 21.3 20.6 17.5 13.8  8.4  2.2 12.1 2379
    1915  2.0  4.9  5.8 13.1 14.9 18.2 20.3 19.8 17.5 13.4  8.2  3.7 11.8 2395
    1916  1.8  3.0  6.5 11.2 15.2 17.9 21.3 20.5 17.0 12.3  7.3  2.0 11.3 2406
    1917  1.3  1.4  5.9 10.4 13.5 18.2 21.1 20.0 17.1 11.3  8.0  1.1 10.8 2426
    1918 -0.4  3.1  8.2 10.8 15.7 19.1 20.3 20.7 16.4 13.7  7.7  4.5 11.6 2451
    1919  3.2  3.2  6.8 11.6 15.3 19.3 21.1 20.4 17.9 12.6  6.8  2.1 11.7 2450
    1920  1.5  3.6  7.1 10.1 15.1 18.6 20.6 20.1 17.8 13.4  7.2  3.8 11.6 2463
    1921  4.0  4.8  9.0 12.1 15.9 19.8 21.7 20.3 18.2 13.4  7.6  4.3 12.6 2528
    1922  1.2  3.0  7.1 11.7 16.1 19.5 20.6 20.6 18.2 13.3  8.1  3.5 11.9 2553
    1923  3.4  2.1  6.1 11.0 15.2 18.9 20.9 20.1 17.6 12.5  8.3  5.3 11.8 2592
    1924  0.9  3.7  6.0 11.1 14.7 18.7 20.5 20.5 16.9 13.6  7.9  1.7 11.3 2628
    1925  1.7  4.9  7.8 12.7 15.3 19.4 20.9 20.4 18.0 11.1  7.5  3.8 12.0 2666
    1926  2.8  5.1  6.7 11.1 15.7 18.5 20.9 20.6 17.3 13.1  7.4  2.9 11.8 2717
    1927  2.4  4.6  7.6 11.5 15.1 18.4 20.8 19.7 17.7 13.8  8.3  1.9 11.8 2716
    1928  2.9  3.9  7.3 10.6 15.8 18.0 21.1 20.6 17.1 13.3  8.1  4.1 11.9 2726
    1929  0.5  0.9  7.8 11.3 15.0 18.5 20.9 20.6 17.2 13.1  7.1  3.5 11.4 2762
    1930  0.3  5.3  7.1 12.4 15.5 19.1 21.6 21.0 17.9 12.4  7.9  3.6 12.0 2787
    1931  3.7  5.1  7.0 11.8 15.5 19.7 21.7 20.6 18.6 14.1  9.0  5.2 12.7 2883
    1932  4.2  4.5  5.9 11.9 15.9 19.2 21.0 20.9 17.8 12.9  7.6  3.4 12.1 2919
    1933  3.9  2.9  7.3 11.5 15.8 19.9 21.4 20.5 18.4 13.3  7.9  3.9 12.2 2953
    1934  4.0  3.7  7.4 12.3 17.1 19.7 21.8 20.8 17.4 13.7  9.2  4.0 12.6 2973
    1935  2.2  4.9  8.0 11.1 14.7 18.6 21.5 20.8 17.5 13.2  7.3  3.1 11.9 2988
    1936  1.2  0.3  7.7 11.0 16.5 19.4 22.0 21.2 18.0 12.9  7.4  4.3 11.8 3051
    1937  1.1  3.2  6.2 11.3 16.1 19.2 21.4 21.4 17.8 13.1  7.6  3.2 11.8 3082
    1938  2.7  4.1  8.7 12.2 15.7 19.0 21.1 21.1 18.2 14.1  7.8  3.8 12.4 3111
    1939  3.5  2.8  7.0 11.5 16.3 19.0 21.2 20.7 18.0 12.9  8.0  5.4 12.2 3147
    1940 -0.0  3.5  7.0 11.2 15.6 19.1 21.1 20.4 17.8 13.6  7.2  4.7 11.8 3181
    1941  2.8  3.9  6.8 12.5 16.2 19.0 21.2 20.3 17.5 13.7  8.6  5.0 12.3 3282
    1942  2.7  3.0  7.8 12.4 15.6 18.9 20.9 20.3 17.4 13.5  8.3  3.6 12.0 3290
    1943  1.7  4.7  6.5 11.9 15.5 18.9 21.0 20.5 17.4 13.4  7.8  4.2 12.0 3329
    1944  3.8  4.2  6.5 11.1 16.2 18.9 20.6 20.4 17.8 13.5  8.2  3.0 12.0 3334
    1945  2.0  3.9  8.8 11.7 14.7 18.2 20.3 20.5 17.5 13.1  7.9  2.7 11.8 3380
    1946  3.2  4.4  9.0 12.7 15.2 18.6 20.8 20.0 17.5 13.1  8.2  4.3 12.2 3436
    1947  3.1  3.0  6.9 11.7 15.5 18.4 20.6 21.0 17.9 14.5  7.4  4.0 12.0 3497
    1948  2.3  3.4  6.7 12.3 15.8 19.1 20.7 20.4 17.9 13.0  8.5  4.1 12.0 3658
    1949  2.6  3.8  7.4 12.2 16.2 19.2 21.1 20.7 17.4 13.7  9.2  4.4 12.3 3950
    1950  2.7  4.4  7.1 11.3 15.9 19.0 20.5 20.0 17.5 14.1  7.8  4.2 12.0 4036
    1951  4.1  5.5  8.1 12.6 16.7 19.1 21.2 20.9 18.2 14.2  8.8  5.7 12.9 4709
    1952  5.1  6.3  8.1 13.4 16.6 20.0 21.6 21.1 18.5 13.8  9.2  5.9 13.3 4872
    1953  5.6  6.4  9.7 12.8 16.7 20.0 21.5 21.1 18.6 15.0 10.0  6.6 13.7 4971
    1954  3.9  7.0  8.6 13.3 16.1 19.7 21.4 20.9 18.7 14.5 10.3  6.1 13.4 5066
    1955  4.8  5.7  8.5 13.4 16.8 19.3 21.6 21.4 18.5 14.6  8.6  5.3 13.2 5058
    1956  4.5  4.9  8.5 12.6 16.6 19.6 20.9 20.5 18.0 14.5  8.9  6.1 13.0 5104
    1957  3.4  6.1  8.8 13.0 16.5 19.8 21.4 20.8 18.1 13.7  9.5  6.7 13.2 5100
    1958  4.8  5.2  8.2 13.0 17.2 19.4 21.3 21.0 18.3 14.2  9.7  5.3 13.1 5123
    1959  3.8  5.3  9.2 13.2 16.8 19.9 21.6 21.2 18.2 13.9  8.5  6.2 13.1 5166
    1960  4.3  5.7  7.5 13.1 16.4 19.7 21.2 20.9 18.5 14.5  9.7  5.4 13.1 5250
    1961  4.2  6.6  9.7 12.9 16.5 19.9 21.3 21.1 18.4 14.4  9.6  5.2 13.3 5468
    1962  4.1  6.0  8.3 13.2 17.0 19.4 20.9 20.9 18.1 14.8  9.9  5.8 13.2 5584
    1963  3.0  5.5  9.2 13.2 16.8 19.7 21.4 20.9 18.6 15.5 10.4  4.6 13.2 5681
    1964  4.7  5.1  8.4 13.2 17.0 19.5 21.4 20.4 18.0 14.0  9.6  5.2 13.0 5718
    1965  4.8  5.4  8.0 12.8 16.7 19.2 20.7 20.4 17.7 14.4  9.9  6.6 13.0 5875
    1966  3.9  6.1  9.6 12.8 16.3 19.4 21.3 20.5 18.0 14.2  9.9  5.8 13.2 5937
    1967  5.0  5.4  9.3 12.9 16.2 19.2 20.8 20.6 18.0 14.6  9.5  5.8 13.1 5947
    1968  4.0  5.4  9.9 13.3 16.1 19.2 20.8 20.2 18.0 14.4  9.8  5.4 13.0 5962
    1969  3.9  5.4  8.2 13.3 16.9 19.0 21.0 20.8 18.1 13.9  9.9  6.1 13.0 5993
    1970  3.8  6.4  8.4 13.1 16.6 19.5 21.1 20.8 18.0 14.1  9.6  5.8 13.1 6001
    1971  4.3  5.9  8.5 12.7 16.1 19.2 20.6 20.5 18.0 14.4  9.6  6.1 13.0 5890
    1972  4.1  5.2  9.4 12.9 16.6 19.1 20.6 20.5 17.7 13.7  9.2  5.6 12.9 5887
    1973  5.0  6.4 10.1 13.0 16.5 19.4 21.1 20.8 18.1 14.5  9.2  5.9 13.3 5944
    1974  4.4  5.8  9.4 13.1 16.2 19.0 20.8 20.2 17.3 13.8  9.6  6.0 13.0 5948
    1975  5.1  5.6  8.6 12.4 16.6 19.1 21.1 20.4 18.0 14.2  9.7  5.5 13.0 5968
    1976  4.0  6.4  8.5 12.9 15.9 18.9 20.4 19.9 17.5 13.0  8.4  4.9 12.6 5820
    1977  2.6  6.4  9.8 13.5 16.8 19.3 21.0 20.4 18.0 14.1  9.9  5.5 13.1 5795
    1978  3.7  4.7  9.0 12.8 16.3 19.1 20.8 20.2 18.0 14.0  9.2  5.3 12.8 5797
    1979  3.2  4.4  9.3 12.4 16.0 19.2 20.7 20.4 18.1 14.3  9.4  6.8 12.8 5746
    1980  4.1  5.2  8.3 12.9 16.5 19.2 21.1 20.6 18.0 13.8  9.9  5.5 12.9 5724
    1981  4.5  6.3  9.5 13.4 15.8 19.1 20.8 20.3 17.7 13.4  9.3  5.7 13.0 5532
    1982  2.6  4.6  8.2 11.8 16.3 18.3 20.4 20.1 17.6 13.7  8.8  6.2 12.4 5354
    1983  4.7  5.9  9.0 12.2 15.8 18.6 20.8 20.9 18.0 13.9  9.4  3.8 12.7 5320
    1984  3.8  6.1  7.9 12.1 15.8 18.8 20.4 20.4 17.0 13.7  8.7  4.8 12.5 5251
    1985  2.8  4.2  8.6 13.1 16.5 18.4 20.5 20.1 17.1 13.5  8.0  3.8 12.2 5193
    1986  4.5  4.7  9.1 12.9 16.3 19.2 20.5 20.1 17.4 13.3  8.0  5.1 12.6 5136
    1987  3.6  5.8  7.8 12.8 16.5 19.5 21.2 20.4 18.1 13.3  9.1  5.6 12.8 5045
    1988  3.3  4.4  8.2 12.5 16.5 19.6 21.5 21.1 17.8 13.3  8.6  4.8 12.6 4998
    1989  4.2  4.0  8.3 12.9 16.2 19.0 21.1 20.5 17.7 13.6  8.4  3.5 12.4 4926
    1990  5.6  6.7 10.4 13.3 16.6 20.0 21.6 21.5 19.1 15.0 11.5  6.9 14.0 4701
    1991  6.6  8.9 11.3 14.4 17.5 19.9 21.1 20.9 18.5 15.1  9.9  7.6 14.3 3743
    1992  7.3  8.9 11.1 14.0 17.1 19.1 20.5 20.2 18.1 14.4  9.2  5.6 13.8 3683
    1993  4.6  4.9  9.0 13.2 17.3 19.9 21.8 21.5 18.2 14.2  8.4  6.3 13.3 3283
    1994  4.4  5.3 10.2 14.1 17.2 20.9 22.2 21.6 19.1 14.9 10.5  7.3 14.0 3250
    1995  5.7  6.9 10.3 13.2 17.0 20.2 22.4 22.4 18.7 15.1  9.6  6.0 14.0 3161
    1996  4.9  6.5  8.7 13.1 17.4 20.5 22.0 21.6 18.3 14.4  9.0  6.6 13.6 3226
    1997  4.6  7.2 10.3 12.7 16.9 20.3 21.9 21.5 19.1 14.7  9.7  6.6 13.8 3182
    1998  6.3  8.4  9.8 14.1 18.1 20.5 22.5 22.2 20.0 15.1 10.5  7.0 14.5 3165
    1999  5.7  7.8  9.7 13.9 17.3 20.4 22.5 21.8 18.8 14.7 11.1  6.9 14.2 3173
    2000  5.2  7.6 10.7 13.9 17.8 20.4 21.8 22.0 18.8 14.7  8.6  4.5 13.8 3151
    2001  3.8  4.9  8.8 13.4 17.3 20.3 22.1 22.3 18.6 14.7 10.8  5.8 13.6 2924
    2002  5.3  6.4  8.8 13.6 16.6 20.9 22.9 21.9 19.5 13.6  9.4  5.7 13.7 2960
    2003  4.3  4.7  9.1 13.2 17.2 20.3 22.4 22.4 18.7 14.8  9.6  6.0 13.6 2941
    2004  3.5  5.7 10.5 13.6 17.4 20.1 21.9 21.1 18.9 14.6  9.7  5.6 13.5 2966
    2005  4.8  5.9  8.7 13.7 16.8 20.7 22.6 21.9 19.5 14.6 10.0  4.8 13.7 2814
    2006  5.3  5.5  8.9 14.0 17.2 20.6 22.9 21.7 18.4 14.1  9.9  6.4 13.7 2793
    2007  5.0  4.9 10.2 13.1 17.6 20.7 22.2 22.3 19.3 15.2  9.3  5.7 13.8 2784
    2008  3.9  5.3  9.3 13.2 16.8 20.5 22.3 21.6 18.8 14.4  9.7  5.1 13.4 2774
    2009  4.1  6.6  9.4 13.5 17.5 20.3 21.7 21.6 19.0 13.8 10.7  5.1 13.6 2702
    2010-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0  NaN 2708
    2011-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0  NaN 2682
    2012-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0  NaN 2528
    AA    3.5  4.8  8.2 12.4 16.2 19.2 21.1 20.7 17.9 13.7  8.8  4.8 12.6
    Ad    0.6  2.1  5.1  9.8 14.2 17.7 19.5 18.9 15.8 11.0  5.9  2.2 10.2
     
    For Country Code ALL
     
    From input file ./data/v3.mean
    
  10. Ian W says:

    First you have probably seen this:
    http://stevengoddard.wordpress.com/2012/05/10/hansen-cheating-in-iceland/

    It would appear that quality control and configuration management are totally absent from any of the maintainers of the world ‘temperature’ data.

    Then of more interest, I must admit to not understanding what is meant by ‘average temperature’ it would appear to be a totally meaningless coefficient. I have a high temperature at 3pm and a lowest daily temperature at 5am so I add them and divide by two – and what have I really got? its meaningless – how long was the temperature at the 3pm level? How long did the temperature stay at the 5qm level? No information.

    Then there is enthalpy. The AGW hypothesis is based on the hypothesis that ‘green house gases’ ‘trap’ (sic) energy leading to a rise in temperature. But temperature is not a measure of energy. It is necessary to know the enthalpy of the air first. A cool misty morning leading to a dry hot summer afternoon – may actually show a DROP in energy in kilojoules per kilogram of the atmosphere over the day. But off go the climate ‘scientists’ measuring and averaging temperature.

    This cannot be an accidental use of the incorrect metric – it must be deliberate. It cannot be accidental that updates to the incorrect metric are all moving the value of that incorrect metric in a way that shows increase in that incorrect metric. It cannot be accidental that ‘adjustments’ to the updates of the incorrect metric are also in the same sense. We are watching a deliberate ploy by these ‘scientists’ that the media are too ignorant to understand.

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