Exposing the faithful's double standard

On the blog where they are attacking my claim that summers are getting cooler, some there are complaining that my TMax profiles, which shows a drop since 1900's, is nothing of the sort. Without "proper" statistical analysis to prove there is a drop there is no way I can make such a claim. So I decided to do a test on these guys and presented this graph:

I presented this as a nice example of a dropping temperature profile. Seems very clear what is happening here, the trend is down. But, no, not to these people. Without a vigorous statistical test there is no way one can conclude this is dropping.

Ok...

At the beginning of that thread at that site, when I initially showed my temp profiles, these people had no problem in accepting that winter TMin was increasing. That, they said, was well within AGW theory. So for these people this graph of increasing TMin is quite acceptable:

Definite trend as far as they are concerned. But look closely at the two graphs. They are the same! All I did in the top graph was to plot the lowest TMin and flip the image so the numbers were positive. Thus the top graph, which they assumed was another one of my TMax graphs, was in fact a TMin graph flipped.

So this test has exposed some interesting conflicts for these people.

If they claim that TMax is not dropping but has to be "properly" stat tested, then they also MUST apply this to TMin, which they fully accept that AGW would produce.

This shows so clearly their bias against TMax dropping. They will go to any lengths to discredit it. So a dropping TMax must be a real threat to the theory or they would not be so blatantly contradictory and require a double standard. Increasing TMin is OK, no stat test needed because it fits the theory, but oh no, we must apply rigorous stats to prove TMax is dropping.

So this test puts AGW into a real vice. They have two options:

1) TMax dropping is only due to "statistical noise" but not TMin it's increase is caused by AGW.

2) All both TMax and TMin profiles are the result of random variations of cycles within cycles producing the trends.

If they go with #2 then the temperature changes have nothing to do with CO2 emissions and AGW is dead.

If they go with #1 and ONLY TMax's profile is by random noise, but not TMin, then they have a serious conflict and double standard. I have shown that give them a TMin graph mirrored to LOOK like a TMax drop, they will demand a stats test be done. But not when it really shows that TMin is increasing.

Hence if a stats test proves that TMax is indeed dropping and dropping due to natural variation of cycles within cycles, then so too must TMins' increase be from normal variation of random cycles within random cycles. Hence #1 gets rejected and #2 becomes the only option left. CO2 has no effect on temperatures.

I thank the guys at illconcidered for playing the game and being test subjects.

Does the temperature profile follow a normalized curve?

You decide.

This is for the 29 stations for all across Canada. I took each station's baseline and subtracted the TMax for every day to get anomalies. I then created a matrix of how many days are at each interger deviation from the baseline per year. Years as columns, deviation degrees as rows and the intersection the number of days. I then did a percent calculation for each cell. That is, the percent of days for each year for each degree deviation (cleans up years with fewer days due to missing data). I then created a bell graph for each year and made this animation. Keep in mind that the area under the bars adds up to 100% for every year.

Canadian Heat Waves Part 4E

Count of Days for each Degree Deviation from Baseline.

To see if there is any change over all in temps, not just the extreme ends, requires a counting of the number of days at each degree C deviation from each station's baseline.

This produces a large matrix of deviations from baseline of a range between -40 and 21 in columns, each year in rows and the count of days in each intersecting cell.

The highest number of days should be around the baseline (zero), and looks like this:

A nice normal distribution curve. Each individual year will show the same shape. But does the apex change over the years? Is "global warming" shifting the apex?

Not over all, however, the 1930's and 1940's has the highest shift in the apex.

Is the count changing for each degree above or below the baseline. That is, if summers are indeed cooling then the number of days at temps above the baseline should be dropping. Indeed they are:

Because there are a different number of over all days in the last years (due to missing records), this was done as a percent of each year's count of records. 5C, 6C and 7C anomalies above the baseline are dropping. Fewer days are in each of those ranges. The drop is steeper with 8C, 10C and 12C above baseline:

15C is a nice example of the 1930's being exceptionally hot with more days in this range than any other time in the past 100 years:

But what about the other end, below the baseline, is that changing with time? Doesn't appear to be, -5C, -10C and -15C deviations are flat trends:

So what is happening is since 1920, at least, there are fewer days in the hotter ranges of the year. Not changes in the mid-range temps. This shows a narrowing of the range of swings in temps. And it is not not just the highest of TMax, but all the range of temps of TMax above the average. Summers are not getting as hot today than they did in the 1930s and 1940's.

So if the above baseline is losing days, but the but the below baseline is not changes, where are those days going? They are going into the range very close to the baseline. This is the change in the share the deviation from the baseline is zero:

So over time since the 1920's at least, the bell shape of each year is tending to narrow with fewer days above the baseline, but taller near the baseline. Something to test for.

Canadian Heat Waves Part 4D

If it's hot one year, what will it be next year?

The heartbeat-like pattern of the hottest TMax of the year begs a question. Can it be predicted what this year's hottest temp will be based on the previous year?

This is station 1111, Chreston, BC yearly highest TMax:

This is one of the few stations that shows an increase in TMax since 1990, but still not near the 1930's and 1940's. But notice the ups, then back downs. Is there at pattern to this? Once one year reaches its highest temps, what is the probability the next year will be higher or lower?

To answer that question I took the highest yearly TMax for each of the 28 stations, and matched it up to the next year's temp, and dumped those records into a new table. 3514 records in total. I then subtracted the main year from the next year (such that if 1900 was 35C and 1901 was 30C the diff would be -5C). Thus a negative number means the following year was cooler, while a positive number means the next year was hotter.

I then added up the total count of each integer TMax, and the total number of each percent lower and got a percent of how likely it was for the following year to be cooler for each TMax.

I then did the same for each percent would be hotter for each TMax to get this plot:

This is what this graph is saying: pick any TMax on the X-Axis, and the blue line is the percent chance the following year will be cooler. While the red line is the percent chance the following year will be hotter. At 42C it's 100% likely the following year will be cooler, but by how much?

At 27C, it's only a 5% chance the next year will be cooler, but a 70% chance it will be hotter, but by how much?

This is the range for each TMax that the following year would be lower:

So if a year is at 40C, there is a 95% chance that the next year will have a cooler maximum TMax of between 2 and 9C (38 t0 31C). So even though there have been cooler TMax in some years below 31C, from 40C there is virtually no chance that the following year will be under 30C for its highest TMax.

This next graph is the reverse. With low TMax for one year, what is the likely range of the increase in the following year?

Combining the two plots, if a year has a TMax of 32C, there is a 40% chance the next year will be higher or lower, and the range would be from 1C to 10C hotter, or from 1C to 5C cooler.

It almost appears that 32C is the mid point. Continuing the pendulum analogy, 32C is the bottom of the swing. Anything either side of that and the tendency is more to move back to 32C than it is to go higher or lower.

Is this median point changing over time? Unfortunately there are not enough data with only 28 stations to evaluate this and plot, so instead this is the matrix of years vs TMax and the number of times in each year for each TMax there are records.

The last test is how often when there is a rise between two years, what is the probability of the the following trend up or down? For this test I took all records where the first year was over 32C (our median) with an increase the following year. I then looked at the number of subsequent years showed a decline, the number of a successive increase and the number of no change. There were 771 records in total, of which 71% showed a drop after a rise. That is, when there was a spike up in temp from one year to the next, the following year after that has a 71% chance of being a drop producing a spike. 23% have a continued increase after the second year and 7% were the same, no change.

Canadian Heat Waves Part 4C

Hottest Day for each year for each station.

This requires a matrix of years as rows, stations as columns and cells as the days that reached the hottest temps. The spreadsheet for that can be downloaded from here.

This is the plot of how many of those hottest days land in each month for each year. If there is any migration of the hottest days moving into other months, the loss of one month should show up as a gain in another. But that is not what is happening. Most of the heat loss, the drop in summer temps, is occurring almost exclusively in July. This means the summers are forming more of a plateau than a crest since 1920.

Canadian Heat Waves Part 4B

Number of days above each degree above anomaly for Part 4:

Canadian Heat Waves Part 4

Top Ten Percent of Hottest Days

29 stations were selected to check for what is happening collectively with TMax. These stations were selected to have a start year before 1920 and have at least 95% of the records within their date range.

These are those stations:

StnID	Station	Province	Starts	Ends	Records	BaseTMax
1111	CRESTON	British Columbia	1912	2006	2700	31.1
1340	VAVENBY	British Columbia	1913	2009	2120	32.4
1835	CALMAR	Alberta	1916	2007	1965	28.2
1957	RANFURLY	Alberta	1905	1991	1613	29.1
2106	LACOMBE CDA	Alberta	1908	1993	1991	28.6
2205	CALGARY INT'L A	Alberta	1900	2009	2626	28.8
2247	GLEICHEN	Alberta	1903	2005	2297	30.2
2364	BANFF	Alberta	1900	1994	2360	27.2
2409	LAKE LOUISE	Alberta	1915	2007	2230	26.
2490	CAMPSIE	Alberta	1912	2009	1998	28.2
2658	BEAVERLODGE CDA	Alberta	1913	2007	1950	27.3
2973	MUENSTER	Saskatchewan	1904	2009	1930	30.1
3259	SCOTT CDA	Saskatchewan	1911	2009	1903	30.6
3270	WASECA	Saskatchewan	1907	2009	1927	29.4
3328	SASKATOON DIEFENBAKER INT'L A	Saskatchewan	1900	2009	2136	31.2
3533	RUSSELL	Manitoba	1912	1990	1631	30.1
3673	SPRAGUE	Manitoba	1916	1997	1533	30.6
380	BELLA COOLA	British Columbia	1900	2002	1859	28.3
3938	FORT FRANCES	Ontario	1913	1995	1346	30.6
3943	MINE CENTRE	Ontario	1915	2005	1562	30.5
3952	DRYDEN	Ontario	1914	1997	1129	29.7
4333	OTTAWA CDA	Ontario	1900	2010	1667	31.5
4547	BRUCEFIELD	Ontario	1903	1993	1115	31.2
5208	BERTHIERVILLE	Quebec	1919	1994	1118	30.5
5348	DRUMMONDVILLE	Quebec	1914	2009	1356	31.
588	FORT ST JAMES	British Columbia	1900	2009	2044	27.2
6158	FREDERICTON CDA	New Brunswick	1913	2000	1327	30.3
6527	CHARLOTTETOWN CDA	Prince Edward Island	1910	1992	1814	27.2

Each station had their top 10% of high TMax from July, regardless of the year, dropped into a table. Those in turn were baselined for each station from 1961 to 1990, the common range used in the science (for what ever reason they give).

From there the anomalies from those baselines were plotted for the entire dataset.

This is the highest TMax anomaly:

The over all trend is down, fewer hot days across all of Canada. The heat waves peaked in the 1940's, dropping until the 1980s, and flat since. 20 years of no change in heatwaves.

This is the average of the TMax anomaly:

Basically flat over all, with the 1920's to the mid 1940's dominating.

The lowest of the TMax anomalies will be very close to a flat line, no fluctuation because this dataset starts from a minumum value for each location to give the top 10%.

This is the number of days in each year. This had to be more restrictive in the stations, 1920 to 2005 was the cut off range. So no stations with a start year before 1920 and no stations with an end year before 2005. This is only 16 stations that met that criteria. If the entire dataset was used the count would be skewed, the numbers too low, because of missing stations in those outside years.

The trend is also dropping. Fewer days in Canada are above the top 10% temperature now than in the mid 1940's.

No matter how you slice the data, either looking at single stations, or collectively from a range of stations across Canada, the over all trend of TMax is to cooler temps.

Canadian Heat Waves Part 3

Why Combining Stations Creates too much Error

In the right video I made at the top I got into the problems that arise when one station is used to fill in the gaps for another station. This post will expand on that to expose the problem more.



To know if one can use one location's data to fill in the gaps of another, the first thing you have to do is to check how the temps differ between each other where there are matching records.



So see what happens I picked to close stations, Belleville Ontario (4442) and Ottawa (4333) and matched the days together and subtracted Belleville's TMax, TMean and TMin for the summer months (May to Sept). Belleville is just south west of Ottawa, about a 2 hour drive.



The difference in the Tmax between these two locations is:

Ottawa was as much as 11.7C warmer than Belleville on the same day. Belleville was as much as 15C warmer on a different day, with the average difference of -0.18C and a standard deviation of 2.55C.

The difference in the Tmean between these two locations is:

Ottawa was as much as 8.1C warmer than Belleville on the same day. Belleville was as much as 11.7C warmer on a different day, with the average difference of -0.63C and a standard deviation of 2.20C.

The difference in the TMin between these two locations is:

Ottawa was as much as 12.8C warmer than Belleville on the same day. Belleville was as much as 13.9C warmer on a different day, with the average difference of -1.09C and a standard deviation of 2.20C.



Using just one year, 1974 (it has a large swing in the difference), this is what the summer TMax looks like. Even part of the season shows asymmetry in the difference.


This is the same year for TMin:


Notice that Belleville has warmer nights than Ottawa. This is because Belleville is on Lake Ontario, Ottawa isn't. The lake is buffering the temps for Belleville keeping their nights warmer than Ottawa.


So if you wanted to use Ottawa to fill in Belleville's missing data, the difference can be as much as 10C with a 65% range of +/-2.2C, a 97% range of +/-4.4C. But it gets more complicated than that. It appears the difference between the two locations is changing over time.

This is the difference in the same day TMax between the two locations per year. The top red line is when Ottawa is hotter than Belleville, the middle black line is the average difference of TMax and the blue line is when Belleville is hotter than Ottawa. Notice over time Belleville's hotter daytime TMax is dropping, less difference, compared to Ottawa.

This is the same graph showing the difference in the TMin temp, summer nighttime temps. Notice over time the two locations are showing less of a difference in temps between them.

So this begs the question. How does one merge records together from different locations to fill gaps when the degree of differences changes with time? You can't without introducing a high degree of error calculated from the standard deviations of matching records, which would have to change as the years progress.

Bottom line is using station data from different locations to fill in gaps is nothing more than guesses at best, and at worst is creating data ex nihilo.

Canadian Heat Waves Part 2

What do we do with missing records?

To get a proper analysis one needs a complete recordset. But that does not exist with EC data. I've got 570 stations downloaded that have data (that many again that did not return any data from EC).

I ran a scan of all the stations and counted all records that have data for each year for each station into one table. This is the actual count of records per year:

Of the 570 stations only 4 have a complete 100% dataset from 1900-2009 for all of Canada.

The spreadsheet of all 570 stations and their stats can be downloaded here.

Then even for those stations that have narrow start dates, not all of them have complete records between the start and end years.

This plot shows the start date vs percent of records they should have. Each dot is a station. Notice so few have complete records.

Expanded view of the above plot.

The claim is made that one can fill in gaps in one station with records from a near by station, combining the two into one recordset. If that was even possible to get anything meaningful from doing that, this data suggests one can't hope to be able to do that until well into the 20th century, losing the beginning years.

So how does one get a long term trend of combined stations to get anomalies with such scant data? There isn't any way to do it, period. This is why one can only look at specific stations.

Canadian Heat Waves Part 1

This will be a four part blog post on different ways of seeing how heatwaves and the hottest days of the year are trending across Canada. This part will look at the process of getting that analysis.

This blog protests why I will be using only 15 stations from across Canada to get a trend. So let's put that to bed right off.

The surface records at Environment Canada are at best pathetic. The number of stations peaked in the mid 1980's. This is the count of stations' starting years:

This graph shows the same trend, except this time the years are on the Y-Axis with the station count in the X-Axis.

Thus if you want 50 stations in the analysis it would have to start in year 1911 to prevent the lower number of stations before that data skewing the results. If you wanted 100 stations, it would have to start in 1930.

Recall that the warming trend that the AGW proponents says is happening is increasing in temps from 1850 to 1945, then a drop until 1975, then an increase since 1975. So starting the analysis too far from 1900 will not show a proper over all trend. Especially if, as we have seen in some of the stations, the warmest and coldest years were in the mid 1920's

Thus there is a trade off. The earliest is best, but that restricts us to 15 records.

The following analysis will look at 15 stations only, those that start in 1900 and have a good set of records. Not all of the stations that start in 1900 have continuous records, some have gaps, but it is the closest we will get to as long a recordset as possible. These 15 are the earliest with the most number of records (few gaps).

The 15 stations are from a wide range of stations across southern Ontario. Station data from the far north is so little so late that, if one wants to make claims of trends, one must put that in context of the duration of the records.

For example, Sach's Harbour, way up in the NWT doesn't have records before the mid 1950's. Hence any claim that the trend is increasing (it hasn't since 1970) is ONLY from the mid 1950's. With no prior data there is no way anyone can know what the over all trend is from 1900. Half that data range is no measure of trends.

This is the 15 stations used for the rest of these posts:

StnID	Station	Province
2205	CALGARY INT'L A	Alberta
2364	BANFF	Alberta
2971	MOOSOMIN	Saskatchewan
3080	CHAPLIN	Saskatchewan
3328	SASKATOON DIEFENBAKER INT'L A	Saskatchewan
3509	MINNEDOSA	Manitoba
380	BELLA COOLA	British Columbia
4333	OTTAWA CDA	Ontario
4442	DURHAM	Ontario
4576	LUCKNOW	Ontario
4862	BLOOMFIELD	Ontario
5168	HALIBURTON A	Ontario
5325	BROME	Quebec
588	FORT ST JAMES	British Columbia
735	CHILLIWACK	British Columbia

The other interesting problem that arises is which months to use. The ideal would be to use just July or August. But hot temps occur in other months, and depending on the method used to define a heat wave or hot day will be influenced by the months selected.

This is Station 5325's TMax range for all years:

Red line is the hottest record setting day (highest TMax in 109 years), the blue line is the minimum TMax, and the black is the average TMax. Notice the crest is mid July, but with a few above 30C prior to and after that.

Two of the tests in the next posts will be choosing a threshold temperature by a relative means. One will be the top 10% of hot records, the other being those above the upper second standard deviation. But including TMaxs from month's prior to the crest will lower the threshold.

Using this station as an example, using all the months the top 10% hottest records will return 1582 records (from a total of 15,812). The month distribution of those records looks like this:

However, looking at this from the percent of days in each month we get this:



So the top 10% of the hottest records will have 20% of those records from July. This isn't really the top 10% as it will get dominated by July temps that are actually below the 10% for July.

The other option is to pick just July for the top 10%. Take the lowest temp found in that, and use any days above that low TMax regardless of the month. If we do that we get the lowest temp at 28.3C, so any records above that value regardless of the month. This reduces the records significantly to 164 records. July still dominates at 75% of the records, but it produces a much closer definition of what constitutes a "hot" day for that location.

The other option is to use the top 10% for EACH MONTH so they are all equally weighed. The problem with that is that in May and Sept the top 10% hottest days aren't when compared to mid summer days.

So the best approach to determine what is a "hot" day is to use July as the baseline to find the lowest temp of the top 10% of July's hottest days, and use that lowest threshold to get all those hot days for that location. This process will also be used to get those temps above the upper second standard deviation.

Hottest Day of the year

Station 2973 hottest day of each year. Y Axis is number of days since Jan 1. Some years will have more than one day share the same highest temp.How does AGW force the hottest day of the year further into the year as both the linear trend (dashed line) and the 10 year moving average show?

Number of hot days per month. Evenly spread between July and Aug.

Hottest day of 1952 was April 28. Then what did the rest of the summer look like? Quite flat shaped, not like a normal year with a crest around July:

What would cause this?

Hottest days of each year since 1900:

Year	MaxOfMax Temp	DayNumber	Date
1904	30.6	204	23-Jul-04
1905	28.9	152	02-Jun-05
1906	30.6	187	07-Jul-06
1908	31.7	206	25-Jul-08
1909	33.3	202	22-Jul-09
1910	32.2	176	26-Jun-10
1911	30.6	169	19-Jun-11
1912	32.2	173	22-Jun-12
1913	27.8	160	10-Jun-13
1913	27.8	161	11-Jun-13
1914	32.8	207	27-Jul-14
1914	32.8	208	28-Jul-14
1915	32.2	219	08-Aug-15
1916	28.9	213	01-Aug-16
1916	28.9	220	08-Aug-16
1917	30.6	265	23-Sep-17
1917	30.6	227	16-Aug-17
1918	33.9	164	14-Jun-18
1919	36.1	196	16-Jul-19
1920	33.3	198	17-Jul-20
1921	32.2	241	30-Aug-21
1922	35	213	02-Aug-22
1923	31.1	166	16-Jun-23
1924	33.3	187	06-Jul-24
1925	34.4	214	03-Aug-25
1926	28.9	235	24-Aug-26
1927	31.1	204	24-Jul-27
1928	32.2	222	10-Aug-28
1929	35	206	26-Jul-29
1930	35.6	235	24-Aug-30
1931	35.6	176	26-Jun-31
1932	32.2	231	19-Aug-32
1933	37.2	225	14-Aug-33
1934	33.3	214	03-Aug-34
1934	33.3	227	16-Aug-34
1934	33.3	145	26-May-34
1935	36.7	225	14-Aug-35
1936	34.4	191	10-Jul-36
1937	37.2	184	04-Jul-37
1937	37.2	185	05-Jul-37
1938	32.8	146	27-May-38
1938	32.8	191	11-Jul-38
1938	32.8	209	29-Jul-38
1939	35.6	191	11-Jul-39
1940	36.1	221	09-Aug-40
1941	41.1	199	19-Jul-41
1942	30.6	202	22-Jul-42
1943	35	187	07-Jul-43
1944	32.8	205	24-Jul-44
1945	34.4	228	17-Aug-45
1946	37.8	210	30-Jul-46
1947	35	208	28-Jul-47
1948	33.3	188	07-Jul-48
1948	33.3	242	30-Aug-48
1949	37.2	217	06-Aug-49
1950	36.7	207	27-Jul-50
1951	31.7	215	04-Aug-51
1952	32.2	118	28-Apr-52
1952	32.2	234	22-Aug-52
1952	32.2	237	25-Aug-52
1953	31.7	194	14-Jul-53
1954	32.8	200	20-Jul-54
1955	33.3	196	16-Jul-55
1955	33.3	198	18-Jul-55
1956	35	161	10-Jun-56
1957	33.9	206	26-Jul-57
1958	35.6	202	22-Jul-58
1959	35	204	24-Jul-59
1961	38.3	227	16-Aug-61
1962	33.3	176	26-Jun-62
1963	33.9	202	22-Jul-63
1964	32.8	193	12-Jul-64
1965	30.6	221	10-Aug-65
1966	32.2	196	16-Jul-66
1967	33.3	222	11-Aug-67
1967	33.3	246	04-Sep-67
1967	33.3	248	06-Sep-67
1968	30.6	170	19-Jun-68
1969	33.3	232	21-Aug-69
1970	32.8	219	08-Aug-70
1970	32.8	153	03-Jun-70
1970	32.8	218	07-Aug-70
1971	32.8	233	22-Aug-71
1971	32.8	217	06-Aug-71
1972	35	241	29-Aug-72
1973	32.2	224	13-Aug-73
1974	33.3	217	06-Aug-74
1974	33.3	199	19-Jul-74
1975	33.9	209	29-Jul-75
1976	32.2	235	23-Aug-76
1977	30	174	24-Jun-77
1978	33.9	221	10-Aug-78
1979	32.8	200	20-Jul-79
1980	32.8	191	10-Jul-80
1981	31	221	10-Aug-81
1981	31	251	09-Sep-81
1981	31	184	04-Jul-81
1981	31	183	03-Jul-81
1982	30	217	06-Aug-82
1982	30	245	03-Sep-82
1982	30	210	30-Jul-82
1983	35	242	31-Aug-83
1983	35	217	06-Aug-83
1984	36	208	27-Jul-84
1985	32	236	25-Aug-85
1985	32	185	05-Jul-85
1986	32.5	174	24-Jun-86
1986	32.5	147	28-May-86
1987	33	165	15-Jun-87
1987	33	207	27-Jul-87
1987	33	208	28-Jul-87
1988	40	157	06-Jun-88
1989	37	201	21-Jul-89
1990	34	217	06-Aug-90
1991	34	221	10-Aug-91
1991	34	242	31-Aug-91
1991	34	220	09-Aug-91
1992	32	226	14-Aug-92
1992	32	227	15-Aug-92
1993	31	171	21-Jun-93
1993	31	209	29-Jul-93
1994	30.5	208	28-Jul-94
1994	30.5	226	15-Aug-94
1995	32	149	30-May-95
1995	32	216	05-Aug-95
1996	33	242	30-Aug-96
1997	35.5	218	07-Aug-97
1998	35	217	06-Aug-98
1999	32.5	236	25-Aug-99
2000	31.5	235	23-Aug-00
2001	36	218	07-Aug-01
2002	34.5	198	18-Jul-02
2002	34.5	194	14-Jul-02
2003	36.5	227	16-Aug-03
2004	31	200	19-Jul-04
2004	31	198	17-Jul-04
2005	32.5	212	01-Aug-05
2006	32	179	29-Jun-06
2007	33.5	210	30-Jul-07
2008	35	237	25-Aug-08
2009	31	266	24-Sep-09
2009	31	164	14-Jun-09