Official temperature records have been maintained in New Zealand since shortly after European settlement began in 1840. Throughout the ensuing 150 years, mean temperature levels appeared to remain stable. But NIWA (the responsible Government agency) has recently questioned the historical record, suggesting a long-term warming trend may have been hidden in the data.
Publications from 18681, 19202 19603 and contemporary records4 indicate that mean temperatures in New Zealand cities have not significantly changed since records began (Tables 1,2,3). Degrees Fahrenheit in the early figures have been converted to degrees Celsius.
Early record
| COUNTRY | EXISTING | PLANNED | FUTURE TOTAL |
|---|---|---|---|
| EU | 468 | 27 | 495 |
| TURKEY | 56 | 93 | 149 |
| SOUTH AFRICA | 79 | 24 | 103 |
| INDIA | 589 | 446 | 1036 |
| PHILIPPINES | 19 | 60 | 79 |
| SOUTH KOREA | 58 | 26 | 84 |
| JAPAN | 90 | 45 | 135 |
| CHINA | 2363 | 1171 | 3534 |
| TOTALS | 3722 | 1892 | 5615 |
*NIWA Mean is the 1971-2000 ‘Normal’, representing current average temperature levels for New Zealand as a whole.
Nine-Station Series 1920
In 1920 D.C. Bates2, then Chief Meteorologist, published figures for the mean temperature of nine towns in New Zealand. These are compared with current NIWA figures2 in Table 2.
Table 2 — Comparison between mean temperatures for New Zealand cities before 1920 and 1971-20002,4| STATION | Years of Data before 1920 | Mean Temperature ºC (Bates) | Years of data 1971–2000 | Mean Temperature ºC (NIWA) |
|---|---|---|---|---|
| Auckland | 56 | 15.1 | 25 | 15.1 |
| Rotorua | 32 | 12.6 | 21 | 12.6 |
| Napier | 29 | 14.3 | 21 | 14.5 |
| Wellington | 56 | 12.9 | 30 | 12.8 |
| Nelson | 31 | 13.1 | 25 | 12.6 |
| Hokitika | 34 | 11.8 | 30 | 11.7 |
| Dunedin | 55 | 10.1 | 28 | 11.0 |
| Queenstown | 9 | 10.1 | 30 | 10.7 |
| Invercargill | 11 | 10.0 | 29 | 9.9 |
| Mean | 12.2 | 12.3 |
It is notable that the averages for six of the nine stations currently remain within one-tenth of a degree of the average temperatures recorded a century earlier—as does the overall average.
24-Station Series 1960
Table 1 — Comparison of mean temperatures for New Zealand cities before 1868 and 1971-2000.1,4| STATION | Years of Data | BEFORE 1868 (NZ Institute) | Years of Data | 1971-2000 (NIWA) |
|---|---|---|---|---|
| Auckland | 15 | 15.7ºC | 25 | 15.1ºC |
| Taranaki | 12 | 13.7ºC | 20 | 13.6ºC |
| Wellington | 10 | 13.2ºC | 30 | 12.8ºC |
| Nelson | 16 | 12.8ºC | 25 | 12.6ºC |
| Christchurch | 11 | 12.8ºC | 26 | 12.1ºC |
| Dunedin | 15 | 10.4ºC | 26 | 11.0ºC |
| Mean | 13.1ºC | 12.9ºC | ||
| NIWA Mean* | 12.6ºC |
It is notable that the averages for more than half of the stations currently remain within 0.2°C of the average temperatures recorded a half-century earlier.
Hessell (1980)
In the late 1970s, a senior meteorologist with the New Zealand Meteorology Service, JWD Hessell, undertook an exhaustive study of climate records, culminating in publication of “Apparent Trends Of Mean Temperature In New Zealand Since 1930”5. He found no important change in annual mean temperature during 1930-80 except in the case of stations affected by changes in shelter, screenage and/or urbanisation.
Seven-station Series (7SS) 1992
In the 1970s, Salinger6-8 introduced the suggestion that certain “corrections” should be made for site changes at the seven longest-established weather stations. His method was based on a comparison with “neighbour” stations, but his calculations are no longer available. The Salinger adjustments would produce a positive upwards trend of approximately one degree Celsius per century.
NIWA later recruited Salinger and adopted his temperature chart in 1992 as the basis of the official New Zealand temperature record. The Seven-station Series (7SS) has since been converted into ‘temperature anomalies’ by subtraction of each annual figure from that location’s NIWA Mean. Figure 1 shows the 7SS chart to 20099.
Unadjusted Seven-station Series 2009
In November 2009, Treadgold10 published a graph of the temperature anomalies for the seven stations depicted in the NIWA official database of historical measurements—excluding the Salinger adjustments. This showed no temperature trend during 1850-2000.
NIWA revision (NZT7) 2010
Recently the mean annual temperature anomaly record in respect of the seven stations has been extensively revised9. The revised record (referred to by NIWA as NZT7) is shown in Figure 1 (here Figure 3).
The Report9 on the revision has 169 pages and many diagrams.
Table 4 summarises the Review results. The note which was included below it shows that all seven stations did not apply until 1913. The “trend” should therefore be 0.97ºC per yr.
Table 4
Summary of review results7
* “This is the trend of the seven-station composite series (Figure 2), not the average of the 7 individual trends (which have different starting years). It is coincidental that the previous and revised trends agree exactly to the second decimal place. For example, had we chosen the period 1913-2009, the trends would be 0.95 °C/century (Previous) and 0.97 °C/century (Revised).”
NZT7 uncertainties
The Report notes that “the 95% confidence intervals on the trends is approximately ±0.3 °C/century”. This high level of uncertainty reflects the difficulty of forcing a trend line on to a curve which does not exhibit any constant trend throughout its length. On further analysis, the graph in Figure 2 reveals three distinct trends.
The Report emphasises that, to date of publication, the error margins have been measured only in respect of the slope of the trend-line.
“It does not include any consideration of uncertainty about each adjustment separately. Further research is under way to quantify how the accumulating adjustments influence the uncertainty in the trend estimates. The individual station documents show the trends separately for each composite.”8
It seems inherently unlikely that the average New Zealand temperature a century ago should now prove to be almost 1.00°C cooler than all the contemporary records suggest. This provides a challenge for the NZT7, which can only be met by robust statistical support.
No useful assessment can be made of the proposed adjustments until the statistical uncertainties are known. Meantime, the NZT7 has replaced the 7SS on NIWA’s website—at least provisionally.
References
1. New Zealand Institute Transactions and Proceedings 1868.
2. Bates, D.C. “Climate and Meteorology of New Zealand” (1920), Wellington, M.F. Marks, 992.
3. New Zealand Meteorological Service “Summaries of Climatological Observations at New Zealand Stations” (1960), Wellington.
4. National Institute of Water and Atmospheric Research Ltd (NIWA) (2010). “New Zealand Mean Monthly Air Temperatures” http://www.niwa.co.nz/education-and-training/schools/resources/climate/meanairtemp
5. Hessell, JWD “Apparent Trends Of Mean Temperature In New Zealand Since 1930” (1980), New Zealand Journal of Science, 23, 2-9.
6. Salinger, M.J. (1981) Site Assessments on Climatological Stations. Appendix C in:
“New Zealand Climate: The instrumental record”. Thesis submitted for the degree of Doctor of Philosophy at the Victoria University of Wellington, January 1981.
7. Salinger M.J. (1982) “On the suggestion of post 1950 warming over New Zealand”. New Zealand Journal of Science 25, 77-86.
8. Salinger, M.J. (1991), “Greenhouse New Zealand,” Square One Press, Dunedin, New Zealand, 104 pages.
9. NIWA (2010). 7 station series review: http://www.niwa.co.nz/news-and-publications/news/all/7-station-series-review
10. “Are We Feeling Warmer Yet” (2009), The New Zealand Climate Science Coalition www.climateconversation.wordshine.co.nz/docs/awfw/are-we-feeling-warmer-yet.htm
11. Leyland, B. (2010) (to be published). ACKNOWLEDGEMENT: Much of the material in this paper was researched and collated by Dr Vincent Gray.
6th February 2011.
Views: 2438
Good summary, Barry. it has always confused me that NIWA insists that NZ has warmed more than the oceans surrounding it in the last 100 years.
“In November 2009, Treadgold10 published a graph of the temperature anomalies for the seven stations depicted in the NIWA official database of historical measurements—excluding the Salinger adjustments. This showed no temperature trend during 1850-2000.”
I’m sure that if a linear trend was applied to the data that it would show a small rise, perhaps 0.2-0.3 C/century.
Richard T, do you still have the spreadsheet plot to to do this? I (for one) would be interested to know the slope.
It seems that every series I look at has has different values prior to about 1930.
Richard,
I’ve just posted it to the site. The file is
Summary AWFWY RTreadgold.xls (46 KB).
The unadjusted trend is level—statistically insignificant at 0.06°C per century since 1850.
Thanks for the trend. I’m curious as to the source of a series starting at 1850. Is it named formally or the result of a paper? Why has this old data been abandoned.
That unadjusted trend really is flat and less than I guessed. I suspect too that there must have been some horrendous adjustments to it.. I’d like to know more about that series.
BTW, the link to the xls file is not working.
– Sorry, a typo. Fixed now. RT
The early data had a lot wrong with it and was very unreliable. The Coalition scientists have been criticising it for years. I don’t think there’s much point in digging around in it, which is probably why NIWA has finally ditched it. The adjustments to it are shown in our paper AWFWY?. For each station, there’s a graph showing the effect of all the adjustments. Some of the older temps ended up nearly a whole degree lower than the actual readings. I think Hokitika suffered the biggest adjustments.
I see, thanks. This old 7SS was replaced by the 7SS which was in turn replaced by the NZT7.
Still good to have the old 7SS data even if it is messy because it provides a starter when looking at CliFlo for data prior to 1909.
I’m hoping that the actual averages (not anomalies) and the stations used are in the xls file but if not, do you have the station composition of this ex-official database of historical measurements?
The data for each station might still be in CliFlo, just not compiled as a series.
I see the xls, thanks. All the stations used are there but just anomalies unfortunately but I can reconstruct my own actuals from the baseline climate hopefully.
This is a valuable series, I can’t see why NIWA are discarding historical data like this.
If you look at the station metadata to see what went on at each station you’ll start to understand why the data is unreliable and why it cannot readily be adjusted to compensate.
They’re not discarding the data, just not using it in the NZT7.
Looking at Summary AWFWY RTreadgold.xls it’s easy to see why the early period was dropped.
Masterton doesn’t start until 1906 and there are long periods prior to then when it’s only a 2SS or 3SS.
This calls into question any paper or study that we can only assume was based on this dataset prior to 1906.
e.g.
Salinger 1995 (what stations did he use for an NZ 6SS 1861-1992 prior to 1906?)
NIWA 2005 (cites Salinger 1995)
IPCC AR4 2007 WGII, New Zealand section, last 140 years (cites NIWA 2005).
“It seems that every series I look at has has different values prior to about 1930.”
Hessell 1980 explains why.
“Many New Zealand climatological stations were established about 1930, there being only a few with unchanged sites and unbroken records before that date.”
The 13.1 C mean Table 1 before 1868 (NZ Institute) is EXACTLY the average mean temperature of NZT7 2010.
Obviously, the Salinger method of adjustments was not applied at NZ Institute and the before 1868 period was in fact waaaaay cooler than 2010.
Hessel 1980
“Apparent Trends Of Mean Temperature In New Zealand Since 1930”
http://investigatemagazine.com/hessell1980.pdf
“A systematic analysis of all New Zealand climatological stations with sufficient length of record reveals that no important change in annual mean temperature since 1930 has been found at stations where the above factors are negligible”
“above factors” being:- changes in shelter, screenage and/or urbanisation.
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Richard Treadgold – thanks for supplying a link to your spreadsheet. This is the sort of data I have been requesting from you for a year and you had refused to provide.
However, there is a huge mistake in your spreadsheet which invalidates your conclusion (this involves calculation of “averages”). The correct unadjusted temperature trend is actually 0.23°C per century, not 0.06°C per century.
This mistake would have been picked up early if you had obtained proper scientific review of your report, or had responded ethically to the request for your data and methods.
I have provided more detail of your mistake in Shonky climate-change denial “science” and welcome your consideration and response.
However, there is a huge mistake in your spreadsheet which invalidates your conclusion
If data is missing, you have two choices:
(1) Ignore it.
(2) Try to guess, or interpolate the data from some other source.
I am struggling to see how there is a “huge mistake” in the calculations.
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Because the calculation of the averages was faulty. No attempt was made to interpolate from any other source or to reconstruct the data. The honest thing to do would have been to remove the data. As it is it gave Richgard Treadgold the wrong information.
It is a huge mistake because it was incorrect to calculate “averages” that way.
I agree that removing sparse data is advisable, but I fail to see how reconstructing the data or interpolating from other sources is any more valid. You either have measurements or you don’t.
So, Andy, you agree Treadgold has made a cock up with the data by not removing the faulty “averages.”?
Why do you put the word “averages” in quotes?
If I take 10 measurements, and 5 are faulty, then a acceptable definition of average is to take the mean of the 5 good measurements.
Am I missing something here?
No, that’s perfectly valid.
If you take the temperature for only 1 station and call it the “average” of 7 stations (effectively what Treadgold has done for many years) then you are a fool.
And analysis after removal if the faulty averages” shows Treadgold’s conclusion to be silly.
Have a look at my analysis.
You could apply the same argument to some of the rather dubious interpolations of temperatures across, for example, the arctic where there are no land stations for hundreds of kilometres.
I guess as long as you state your assumptions and apply caveats then the interpretation can be left up to the reader of the reports.
Perrott has shot himself in both feet. He supports the 7SS and 11SS, in which NIWA average data over multiple years including those that have missing data. He has been defending them with total myopia and dedication for over 12 months. Now, he has belatedly decided that he doesn’t like NIWA’s approach.
The 11SS is most egregious example ever of a series whose trend is WHOLLY driven by missing data. Seven stations missing in 1931, three missing in 1941, one missing in 1951 and 1991. There is no trend at all shown by the years which have no missing data.
Compare this with Perrott’s criticism of AWFWY – where the missing data moved the trend by less than 0.1°C.
Ken,
So you would require us to ignore the available data and instead make a guess. That’s not very scientific.
What’s your opinion of Salinger’s/NIWA’s adjustments taking the raw readings from an insignificant warming of 0.23 °C per century to a whopping 0.91°C/century? With about 90% of the adjustments favouring an increase in warming?
No Richard. If you are not capable of using statistical methods to interpolate just delete the shonky “average.” That’s what I did.
You should have had your report reviewed or made your data and methods available. This silly mistake would have been picked up for you.
And Richard, even you acknowledged here the need for adjustments when site situations changed. (Which just shows that your slanderous claims in the report were intentionally malicious).
Or have you gone back on that?
Ken,
I never claimed that adjustments were not required, only that no need for large adjustments were apparent in the metadata then available in NIWA’s database. The actual sentences from our report are:
That quite clearly means we found no reasons in the station histories for large adjustments.
So Andy, you agree that Treadgold was wrong not to “state [his] assumptions and apply caveats.”? He didn’t provide any method descriptions.
Was he also wrong not to make his data and methods available to allow proper scientific scrutiny? He has only got that scrutiny now because he made a mistake and allowed access to this one spreadsheet.
Just imagine what other mistakes we would find if he allowed access to the rest?
Ken,
I am not going to get involved in any personal battle that you may have with Richard.
There may be procedural issues that I could disagree with, but I haven’t really looked into the 7 station series in much detail and I don’t feel educated enough to comment on the details.
I have read the recent articles, in particular from Barry Brill, and feel that there are a number of question marks over the methodology in the NZ temperature record.
On a more general note, agree with your sentiments on openness and transparency in data and methodology. I have worked in software development for over twenty years, where this is expected and encouraged.
However, I do see a lot of double standards applied here, particularly pertinent is the recent case of the Steig et al paper on Antarctica temperature records that has featured in the climate blogosphere over the last week or so.
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Ken, not only are you barking mad but you are barking up NIWA’s tree as well as Richard T’s.
Please refer to NIWA’s methodology for the NZT7 series:-
————————————————————————————
1) 7-Station Composite Anomaly = Average of anomalies at individual sites where there is data for that year (<7 sites before 1913)
2) 7-Station Composite Temperature = 7-Station Anomaly + Average of 7-Station 1971-2000 climatologies
E.g., for 1909 when there are 4 sites, the 7-Station Composite Temp is NOT the average of the Wellington, Nelson, Lincoln and Dunedin values.
3) The climatologies are specific to the "Reference" stations at each location, which are: Auckland Aero (Auckland), East Taratahi AWS (Masterton), Kelburn (Wellington), Hokitika Aero (Hokitika), Nelson Aero (Nelson), Lincoln Broadfield EWS (Lincoln), and Musselburgh EWS (Dunedin).
———————————————————–
Note that for the composite anomaly, there is no attempt to compensate for missing data and the composite is a simple average of whatever data is available..
The composite temperature is treated much differently but again there is no attempt to compensate for missing data before the 4-7 station anomaly average is added to the average of 7-Station 1971-2000 climatologies and even then there is not that much difference to a simple average.
You better get on the phone to Dr David Wratt tomorrow and inform him that the NZT7 is "shonky" and whoever compiled the NZT7 is a "fool" according to your "statistical methods" which consist merely of deleting real data or applying the Hansen method of data invention.. You mention interpolation but is that acceptable across stations? A reference station is for comparison, not for transfer. Within a station history however, interpolation is reasonable but what is the cutoff? 2 years? 3 years? 5 years? But even then, interpolation does not make assumed data any more accurate than a guess.
To compensate for missing data is a an issue that not even NIWA is addressing but if they were, it's a little more involved than your method.
If the NZ geographic area is to be represented then all data is relative to the NZ land mass centre-of-area . If say Masterton was missing data, the only way to compensate is to delete a corresponding value for Hokitika to restore balance in the series, This is assuming that the series is geographically balanced to start with, The NZT7 is unbalanced geographically in 1909, 1912 and 1919. The inclusion of Lincoln should maintain balance about the centre-of-area for when all 7 stations have data, that is if NIWA has got the spatial analysis right (who knows for sure that they have?) because there is a greater area of land in the south.
So you see Ken, compensating for missing data in the case of NZ temperatures is more of a spatial issue than a statistical issue but this does not seem to be a concern to NIWA and its NZT7.
Now I'll leave you to draft your retractions and apologies for quite a list of scurrilous assertions that you've racked up here, It may pay to engage your brain and do a little research before a repeat performance in future because this last effort really displays a lack of acumen and civility.
2) is misleading because where there is 7 stations available, composite temp is just a simple average of the 7 stations actuals. It is only where there is less than 7 e.g. 1919 that the anomaly method is used but in the case of 1919 the difference is only 0.03 C between a simple average of 6 stations and the method in 2).
Interesting too, that the CliFlo database lists this data available for Masterton (the 5th field is % complete):-
36735 D0596H 01-Mar-2009 31-Jan-2011 100 Masterton Aero Aws -40.975 175.638
37662 D05974 01-Oct-2009 31-Jan-2011 70 Masterton, Te Ore Ore Cws -40.957 175.707
7578 D05973 01-Sep-1992 30-Sep-2009 100 Masterton, Te Ore Ore -40.957 175.707
17466 D0596E 01-May-1999 31-May-2002 90 Masterton Intermediate School -40.958 175.67
2446 D05872 01-Jul-1923 31-Jul-1961 90 Masterton, Bagshot Stn -40.8751 175.76813
But a database 2000-2011 query returns this (02 is the code for temperature):-
Masterton, Te Ore Ore 2000 2 12.3
Masterton, Te Ore Ore 2002 2 12.4
Masterton, Te Ore Ore 2004 2 12.2
Masterton, Te Ore Ore 2005 2 13
Masterton, Te Ore Ore 2006 2 12.4
But NZT7 has this:-
2000 12.47
2001 12.77
2002 12.47
2003 12.54
2004 12.33
2005 13.03
2006 12.41
2007 12.64
2008 12.90
2009 12.40
The data is not interpolated or extrapolated within The Masterton station data so data must have been obtained from some other source. Note that the NZTR values are warmer than the CliFlo data. Are NIWA transferring data from reference stations elsewhere?
That was just the first check I made to see how NZT7 data compares to CliFlo data.
Note also that the introduced years of 2001, 2003, 2007, 2008 and 2009 are considerably warmer than the adjoining CliFlo valus.
Gareth at HT has dutifully regurgitated Ken’s “unmasking” of this “fraud” (their words, not mine)
I’ve duplicated my first comment in this thread at Open Parachute and saw Gareth’s unquestioning “Well done Ken. Persistence pays!” comment above mine. His HT post is equally vacuous.
BTW. NiWA’s 2) above is misleading because where there is 7 stations available, composite temp is just a simple average of the 7 stations actuals. It is only where there is less than 7 e.g. 1919 that the anomaly method is used but in the case of 1919 the difference is only 0.03 C between a simple average of 6 stations and the method in 2).
But they don’t infill the missing data, instead they apply the existing anomalies to a reference climatology which seems unnecessary to me..
I suspect that data infilling is carried out in a more subtle way in the NZT7 by use of reference stations. My contention is that reference stations are for comparisons, not transfers.
I’m looking through CliFlo for CliFlo-NZT7 comparisons. Watch for a post to come on this that Richard T will put up after Barry Brill’s next post (involves Salinger 1995 and tree rings – Hunter and Mackie swear by them). I’m working on a follow up to that now that compares the Salinger’s 1864 10SS, NZT7 and CliFlo data. There’s much more to come on this.
Richard C
Is the NIWA method in (2) simply equivalent to inserting a zero anomaly figure? So, when averaging temps, they include the Normal of any missing station.
To be consistent, anomalies in (1) should be treated the same way. eg in 1909, notional zeroes should represent the three missing stations and the total should be divided by seven. Is this what NIWA does?
Australis, they haven’t phrased it well. Have a look at the data though, and it becomes obvious. Say they have only 4 station for the year. What they do is they calculate the average anomaly for that year by averaging the 4 station anomalies. All good so far. This is the value for the year, and the one they plot.
However, when you come to calculate the average temperature (not the anomaly) they must add their 4-station anomaly obtained above to the average temperature for the whole 7-station series (1971-2000).
Otherwise if they average the 4 station temperatures together, they might get the wrong average. For example, if all 4 stations were by chance in the South Island, the average of those 4 would be lower than the national average.
Bob, I’ don’t think that this is how the NZT7 “Reference Stations” are compiled (there’s 7 – not 1):-
“However, when you come to calculate the average temperature (not the anomaly) they must add their 4-station anomaly obtained above to the average temperature for the whole 7-station series (1971-2000).”
The NZT7 method says this:-
3) The climatologies are specific to the “Reference” stations at each location, which are:
Auckland Aero (Auckland), East Taratahi AWS (Masterton), Kelburn (Wellington), Hokitika Aero (Hokitika),
Nelson Aero (Nelson), Lincoln Broadfield EWS (Lincoln), and Musselburgh EWS (Dunedin).
Also, the NZT7 station values for say Lincoln are not necessarily all from Broadfield EWS. The climatologies of the reference seem to be a separate exercise.
This is probably done to ensure that adjustments don’t influence the climatology values, fair enough. But we must also assume that the reference station in each case has data from the full 1971-2000, no? Bit tricky otherwise.
Tricky yes.
I checked Lincoln, Broadfield Ews in CliFlo but it doesn’t have 30 years of data:-
17603 H32645 01-Jul-1999 31-Jan-2011 100 Lincoln, Broadfield Ews
I really don’t understand these “Reference Stations”. It seems to me that it is a separate dataset that should be published along with the series. How for example, did they compile 30 years 1971-2000 with just 1 1/2 years of data from CliFlo for Broadfield Ews?
There seems to be some other mystery data source.
Barry Brill briefly covers Reference Stations in the post but I’m not much wiser.
A similar thing is happening in the NZT7 series. Way up-thread I checked CliFlo for Masterton 2000-2011 but the years of data available was not contiguous although NZT7 was but the introduced data did not look right.. I don’t get it.
No, Barry covered “Neighbour” stations in the last post – not Reference Stations. They are quite different in function and purpose.
In each location, the default procedure is to bring all past temps into phase with the current “open” station. But then, for various reasons NIWA prefers the second-to-last station instead. The selected site becomes the “REFERENCE SITE” for that location. This means that the 1971-2000 temps of THAT site become the Normal for the location. All anomalies at that location are now found by subtracting the Reference Site Normal from the temp data.
Australis, that helps tremendously.
In the case of Lincoln, the station Broadfield Ews is stipulated as the Reference Station, but there is only 1 full year in CliFlo.
This is the data returned from a query on 17603 Broadfield Ews
Lincoln, Broadfield Ews 2000 2 11.9
The other Open (but no longer being updated) station at Lincoln is Broadfield Edl
4882 H32642 01-Jun-1987 30-Apr-2000 100 Lincoln, Broadfield Edl
A 1971-2000 query of that station returns this data:-
Lincoln, Broadfield Edl 1988 2 12.3
Lincoln, Broadfield Edl 1989 2 12.1
Lincoln, Broadfield Edl 1990 2 12
Lincoln, Broadfield Edl 1993 2 10.8
Lincoln, Broadfield Edl 1994 2 11.3
Lincoln, Broadfield Edl 1995 2 11.8
Lincoln, Broadfield Edl 1996 2 11.6
Lincoln, Broadfield Edl 1997 2 11.6
Lincoln, Broadfield Edl 1998 2 12.5
Lincoln, Broadfield Edl 1999 2 12
And the Closed station 4881 H32641 01-Jan-1881 31-Dec-1987 100 Lincoln returns this data,
Lincoln 1971 2 12.1
Lincoln 1972 2 11.4
Lincoln 1973 2 11.9
Lincoln 1974 2 11.4
Lincoln 1975 2 11.6
Lincoln 1976 2 10.4
Lincoln 1977 2 10.8
Lincoln 1978 2 12.1
Lincoln 1979 2 11.6
Lincoln 1980 2 11.5
Lincoln 1981 2 11.9
Lincoln 1982 2 11.4
Lincoln 1983 2 11.2
Lincoln 1984 2 11.6
Lincoln 1985 2 11.9
Lincoln 1986 2 11.5
Lincoln 1987 2 12
If what you say is correct that “the default procedure is to bring all past temps into phase with the current “open” station” then the Reference data for Lincoln is 10 years of Broadfield Edl and 17 years Lincoln 4881 brought into phase with 1 year of Broadfield Ews.
So 3.33% of the baseline data comes from the last Open (and stipulated) station but 96.66% of the data comes from other stations. This does make sense because the 2 earlier stations are better representations of the climate 1971-2000.
The allocation of “Reference Station” to Broadfield Ews is something of a misnomer IMO, if I am understanding this correctly. A better stipulation would be Lincoln 4881 because it provides 56.66% of the data for the baseline.
Australis. No, there’s no 0 equivalent. If say there’s only 6 station values across a 7 station composite then the 6 anomalies are averaged (total / 6) for an anomaly composite.
For an actuals composite, if all the 7 values are there its a simple average of the actuals. If say 1 value is missing then the average of the 6 anomalies is added to a reference to obtain actual temp. I’ve done a few checks on my understanding using NZT7 data but it would be better for you to do some some yourself to get a feel for it and you may even find I’m putting you crook (i.e. don’t believe everything you read on the internet)
Bob D has explained well but there is also this on the NIWA site:-
——————————————————————————————————————————
Technical note on the treatment of missing data in the 11-station series
http://www.niwa.co.nz/news-and-publications/news/all/2009/nz-temp-record/temperature-trends-from-raw-data/technical-note-on-the-treatment-of-missing-data
Missing months during the year
* Calculate the monthly anomalies by subtracting the climatology for that month (in this case the 1961-1990 average), then
* Average the monthly anomalies to obtain the annual anomaly, ignoring missing months.
Missing annual values or missing sites
The ‘eleven’-station average is simply the average of the individual station anomalies over those stations where the annual anomaly is available.
This is a very important point, often misunderstood. Averaging the anomalies (deviations from climatology at each site respectively), and not the actual temperatures, means that no bias is introduced if the number of cold versus warm sites fluctuates during the period of analysis. For example, over the period 1931-1937, Palmerston North is colder than Queenstown in ‘anomaly’ terms, even though Queenstown is colder by about 3 °C in absolute terms. Using the absolute numbers will bias the results; using the anomalies will not.
—————————————————————————————————————————–
A way to view this is that missing months is a longitudinal calculation but missing years is a cross-sectional calculation (think in terms of a spreadsheet)
This is reasonable to me but I’m not a fan of anomalies because it’s just a convention. The baseline is a standard 30 years that moves every 30 years (currently 1971-2000 I think) but I have seen 30 yr baselines placed arbitrarily at the end of a series for convenience. From what I can gather, the thinking with the convention is that climate changes every 30 years which may well be close to the truth given that 60 year cycles have been extracted statistically from global temp series.
The composition of the reference baseline becomes very important when using anomalies but I’d bet most people don’t give the baseline much thought. It’s really a form of data smoothing I think. So-what, if a warm or cool bias accrues, isn’t that the point of the exercise – to obtain a representation of what is happening to temperatures? But note this is just a personal opinion and to be taken with a grain of salt.
What happens is that as a series gets longer, the 30 yr baseline gets proportionately less than the series length so its OK when the series is not that much longer than the baseline but then the anomaly gets progressively irrelevant as the series lengthens. It also makes comparison of series with different baselines a real mission and in that case the best way is to convert to actuals.
As far as I’m concerned with temperature, the baseline is 0 K or 0 C and I much prefer to use actuals but I’m willing to conform to anomaly convention where appropriate.
According to the WMO handbook, it’s 3 years. And you don’t interpolate, you simply ignore the gap. A gap longer than 3 years invalidates the average. You must use the post-gap data only.
3 years, ignore the gap, post 3+ year gap for an average – gottit, thanks Bob.
There is a problem though if a 2 station series is compiled of say 1 NI station and 1 SI station. If there is a missing value for the NI station, the SI station becomes the composite value when an average is calculated of the two stations making the resulting value unrepresentative of NZ (probably too cool). Is there a convention for this situation?
The EMD utility that I use automatically infills a missing data point by duplicating the previous data point for signal decomposition. I think it’s a horses-for-courses thing, if it’s appropriate to follow a convention them best to do so but there will be exceptions and oftentimes a widely used software package becomes the convention if something different is hard-wired into it.
“if a 2 station series is compiled of say 1 NI station and 1 SI station. If there is a missing value for the NI station, the SI station becomes the composite value when an average is calculated of the two stations making the resulting value unrepresentative of NZ”
It’s impossible to calculate a “NZ average temp” at any time, so one has to make do with proxies – such as seven geographically-spread stations. In a long series, one is more concerned with variations and trends than whether the absolute temp of the seven remains (or ever was) perfectly representative of the country.
It should remain true to the seven, of course, and the standard says up to three years is a tolerable gap. Because the 7SS frequently used gaps of more than three years, as in the pre-1909 period, it was unscientific and wrong. NIWA haven’t yet acknowledged this.
“It should remain true to the seven, of course, and the standard says up to three years is a tolerable gap. Because the 7SS frequently used gaps of more than three years, as in the pre-1909 period, it was unscientific and wrong. NIWA haven’t yet acknowledged this.”
Not quite I think.
The standard (as I understand from Bob D – haven’t read it myself) is that the 3 year gap guideline is for calculations within one stations history (e.g. monthly values added to obtain annual averages), not across several stations (I could be wrong).
I do agree on the spatial issue however. I think it is far more important to retain spatial balance about the centre-of-area than to haggle over missing data. If say there were 3 SI stations and 1 NI station, then 2 SI stations should be dropped and the 1 that is retained should be diagonally opposite across the centre-of-area to the NI station. Otherwise the average of the 4 stations is really only representative of northern SI.
Well done Richard C, like you, I spotted Ken’s mistake the first time I read it. I sat there looking at what he had written thinking “He can’t be that dumb! Surely he checked?!”
But no, he just rushed into print. Tut.
Of course, it shows Gareth up too. Why didn’t he pull Ken quietly to one side for a quiet chat?
Well said!
Manfred at Open Parachute made a similar observation and put his point more concisely using other series e.g. 11SS than I did but our points are compatible.
Doug Mackie has joined GR in a sycophantic gush of irrationality that tries to implicate Chris de Freitas. Why don’t they think before going off half cocked?
I sometimes shake my head in wonder. I trust Ken, Gareth and Doug will be issuing an unreserved apology soon.
But then again, I won’t be holding my breath.
Correction
“The composite temperature is treated much differently but again there is no attempt to compensate for missing data before the 4-7 station anomaly average is added to the average of 7-Station 1971-2000 climatologies and even then there is not that much difference to a simple average.”
Should read
The composite temperature is treated much differently but again there is no attempt to compensate for missing data before the 4-6 station anomaly average is added to the average of 7-Station 1971-2000 climatologies and even then there is not that much difference to a simple average.
(4-7 changed to 4-6)
Funny isn’t it?
You use a bit of common sense about averages and it all gets backed up in NIWAs own procedures. What a strange world we live in.
Remind me again, what exactly is this strawman we are trying to destroy?
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