Showing posts with label ECCC. Show all posts
Showing posts with label ECCC. Show all posts

Maximum Temperature Trends in Select Canadian Cities - Long-Term Trends from Environment and Climate Change Canada's AHCCD Dataset

A previous post reviewed Environment and Climate Change Canada's Adjusted Homogenized Canadian Climate Data (AHCCD) and temperature trends in Toronto and Ottawa. See post: https://www.cityfloodmap.com/2017/11/tvo-articles-on-climate-change-extreme.html

Temperature changes have been related to extreme rainfall changes, given the higher water holding capacity of warmer air.

This post presents more trends in annual maximum daily temperature at 12 cities across Canada. The AHCCD has recently been updated in 2020 - see summary here: https://www.canada.ca/en/environment-climate-change/services/climate-change/science-research-data/climate-trends-variability/adjusted-homogenized-canadian-data/surface-air-temperature.html

The following charts present the annual maximum temperatures (blue line) and 30-year moving average trends (grey line). Years with missing summer data have been removed. The selection of stations is based on those with long records but is not exhaustive. It is not clear if urban heat island effects could be a factor at these stations as well.

In Calgary the period up to the 1940's and 1950's was warmer (had higher maximum daily temperatures) that the most recent period:


In Chilliwack, temperatures have been fairly steady up until the periods ending in the 2000's after which some very high extremes have occurred:


In Fredericton the 30-year rolling average of maximum daily temperature has been increasing since the period ending in the 1930's, but has been decreasing since about 2000:

In Halifax, the average maximum temperatures here highest in the periods before about 1960, after which there was a drop. Since that drop the average has been increasing since 1990:



In Moncton, the average maximum temperatures have been relatively flat:

In Montreal, pre-1910 had lower daily maximum temperatures on average. Since the 1930's average maximum temperatures have been flat:



In Ottawa, the 30-year average has been decreasing since the late 1800's and early 1900's:


In Saskatoon, the 30-year average of maximum temperatures increased up to1940 and has been decreasing since then:


In St. John's, the daily maximum temperatures decreased in the late 1800's but overall have since been increasing, with a slight recent decrease:

In Vancouver, there appears to be a discontinuity in the data, with no trend up to 1930, a steep increase up to 1960, and generally flat (slightly increasing) trend since then:


Ross McKitrick, Department of Economics and Finance, University of Guelph, has commented on Vancouver temperature trends in the past (see July 2019 article in the Vancouver Sun - link: https://vancouversun.com/opinion/op-ed/ross-mckitrick-reality-check-there-is-no-climate-emergency-in-vancouver). He wrote:

"Temperature records for Vancouver begin in 1896. Looking at the 100 years from 1918 to 2018, February and September average daytime highs rose slightly, at about 1.5 degrees per century, while the other 10 months did not exhibit a statistically significant trend. Looking at the interval from 1938 forward, no month exhibits a significant upward trend in average daytime highs, in fact four months went down slightly. Looking at 1958 to the present, four months warmed slightly, but the annual average daytime high did not exhibit a significant trend." - the chart above supports this observation with annual maximum temperatures 'flat' since the late 1930's.

In Winnipeg, average maximum temperatures have been decreasing since the period ending in about 1950:


In Toronto, the trend is similar to Winnipeg - there were increases up to the periods ending in about the mid 1930's then a decrease: 


The previous post, based on data up to 2018, showed the trends in July daily maximum temperatures for other southern Ontario climate stations including Welland, Vineland, Hamlton, Belleville, Toronto and Peterborough. The trends included increases and decreases and an average increase of 0.17 degrees Celsius at these 6 stations:


 

Additional reading: Ross McKitrick has done a more thorough analysis of Canadian temperatures in his paper "Trends in Historical Daytime Highs in Canada 1888-2017" in 2018 (link: https://www.rossmckitrick.com/uploads/4/8/0/8/4808045/temp_report.pdf). He noted trends across Canada similar to those for southern Ontario above, writing "Since 1939 there has been virtually no change in the median July and August daytime highs across Canada, and October has cooled slightly."

Previous posts explored whether extreme rainfall intensities have increased in Canada - recent updates in Engineering Climate Datasets show no recent increase in 100-year design intensities and longer-term trends in southern Ontario stations have not shown increases in those extremes overall. It is possible that the lack of consistent increases in extreme temperature could be related to the trends in extreme rainfall - of course the charts above are limited to annual maximum daily temperatures and not longer-period temperatures that could also be influencing design rainfall intensities. 

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How do you analyze temperature data in the AHCCD? 

Some manipulation of the raw AHCCD information is needed to determine annual maximum temperatures and to assess the 30-year trends charted above. The AHCCD data is provided in a compressed 'zip' file that contains individual files for each location, or climate station. Individual files are text files in ASCII format and are named after the climate station ID #. For example Toronto's station ID 6158355 has a data file called dx6158355.txt that looks like this:



This data file can be imported into an MS Excel worksheet and then be parsed, converting long text strings in column A to separate columns (use Text to Column function). Parsed data, with a column title added to the "data code" column after each day's maximum daily temperature data, would look like this:


Each row of data starting on Row 5 above represents the daily maximum temperatures in a single month. The maximum temperatures for each month can be calculated in column BN using the MAX function. For example, the red text shows maximum temperatures in each month (the maximum daily temperature across the row):


To determine the maximum temperature each year, the Excel Pivot Table function can be used. After selecting the column heading Row 4 and all data rows below and Columns A to BN, insert Pivot Table on a new worksheet. In the Pivot Table Fields window, drag "Annee" (year) into the Rows box and drag "Daily_max" into the Values box. The Values field will by default assign a sum function showing "Sum of Daily_max", summing all the monthly maximum temperatures in each year -  change that to a max function by clicking on the field and setting value field setting to "Max":


The result of the Pivot Table is shown below, with the maximum daily temperature determined for each year:



The annual maximum temperatures can be charted using an XY scatter plot in Excel. To create the 30-year moving average trend, insert a trendline (right click on the plotted line and select "Add a trendline").  Change the trendline type of moving average, specifying "Period" of 30 to average 30 years of annual maximum values (i.e., the overall maximum temperature climate trend for the prior 30 years). 

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Extreme heat and trends can also be characterized using other statistics besides annual maximum temperatures reviewed above. For example, the number of days over a threshold value, such as 30 degrees Celsius, and that would be associated with stresses can be used as well.

The AHCCD data assessed above can be used to count the number of days in each month reaching over a threshold temperature, and those monthly counts can be summed for each year in the record. The example charts below show the number of days in each year with maximum temperature over 30 degrees Celsius. These charts also show the 30-year moving average of number of days over 30 degrees.

In Toronto, the average number of days over 30 degrees was highest many decades ago. The dashed black line shows this average and the ECCC AHCCD data shows that in the 30 years up to 1959 there were 14.9 days above 30 degrees, while in the 30 years up to 2020 there were fewer at 14.0 days a year. In the periods up to 1938-1941 the average number of extremely hot days was also high than the recent past, with 14.4 days above 30 degrees for those earlier periods: 


In Calgary, similar analysis shows that earlier periods were hottest. The 30 year average up to 2020 has an average number of days above 30 degrees of 4.8, compared to the period up to 1941 that had 6.1 days. The recent average of 4.8 days was exceeded in all the periods up to 1933 to 1955, and the periods up to 1986 to 1989 as well: 



Annual Maximum Rainfall Trends in Canada - Environment and Climate Change Canada's Updated V3.20 Datasets Show Few Significant Trends

Previous posts have presented overall trends in annual maximum observed rainfall amounts at Canadian climate stations (link: https://www.cityfloodmap.com/2020/12/design-rainfall-trends-in-canada.html).

Environment and Climate Change Canada (ECCC) periodically updates trend analysis on the annual maximum series (AMS) for each station, and these series are used to derive design intensities, i.e., Intensity-Duration-Frequency curves. Data area available here (link):  https://climate.weather.gc.ca/prods_servs/engineering_e.html

In May 2021 additional analysis has been included in these Engineering Climate Datasets. The "Whats_New_EC_IDF_v3-20.pdf" file includes a summary table that provides counts of stations and additional station years added with recent update:

The v-3.20 update adds 490 station-years of data. There are currently 17,133 station-years of data. The average length of record is 25.3 years. This represents a slight decrease in record length compared to 25.5 years in v-3.10, as new short record stations are factored in.

Trends in annual maximum rainfall have not change all relative to the 2020 v-3.10 data. The majority of station data show no statistically significant trend. The table below compares trends in earlier datasets, averaged across all durations. 

Trend in Maximum Rain    v3.20       v3.10       v3.00         v2.30

Significant Increase              4.16%     4.28%       4.18%        4.09%

Significant Decrease             2.25%     2.24%       2.33%        2.30%

No Significant Trend          85.73%    85.80%     85.55%      86.37%

No Calculation                      7.86%      7.68%       7.94%        7.24%

 

The v-3.20 datasets  have the following trends within various durations:


Excluding 'No Calculation" data, annual maximum observations with 'No Significant Trend' represents 92-94% of series, with an average of 93.0%. Excluding the 'No Calc' data results in an average of 4.5% significant increases and 2.5% significant decreases.

The following chart shows that majority of station data show no statistically significant trend.



There has not been any appreciable change in the annual maximum rainfall trends considering earlier datasets (see v-2.30 to v-3.00 update https://www.cityfloodmap.com/2020/02/annual-maximum-rainfall-trends-in.html)

In Canada, the number of stations with annual series used to derive extreme rainfall statistics continues to increase. A previous post explored how manually-operated climate stations have been declining while this increase occurs (link: https://www.cityfloodmap.com/2020/06/do-we-have-enough-climate-stations-in.html). In 1990 there were only 11,268 station-years of data. Today with 17,133 station-years of data we have 52% more information to guide assessments of extreme rainfall.  

This table summarizes the rise in climate station count and rise in station-years as new data is added.


Some have confused the decline in manual stations with a decline in overall data (see the above post). This chart shows the rise in climate stations with IDF data used for engineering design (orange lines), along with the decline in manual station data (blue bars).






Annual Maximum Rainfall Trends in Canada - Engineering Climate Datasets v3.00 and 2.30 Comparison

This blog has reviewed annual maximum rainfall series trends in the past, including all the v2.30 Engineering Climate Dataset trends across Canada.  Also v3.00 trends for stations with long term records and southern Ontario derived IDF trends for long-term stations.

Overall most trends are not statistically significant and the few percentage of significant increases and decreases can be explained largely by chance.  The follow charts compare the trends for all Environment and Climate Change Canada's Canadian stations using the v2.30 data and the newest v3.00 data release in winter 2019.

Maximum rainfall trends in Canada.  Environment and Climate Change Canada's Engineering Climate Datasets.
What do the charts show? Not much change after adding 15% more stations and up to 10 years more data. The following tables illustrate the percentages of significant ups and downs (red and green bars), non-significant changes (the grey bars) and no data (not shown in the charts).

Maximum rainfall trends in Canada - Direction and Statistical Significance.  Environment and Climate Change Canada's Engineering Climate Datasets v2.30 and v3.00 Comparison.
The data show that in v2.30 over 86% of trends were not significant. In v3.00 a bit fewer statistics were non-significant.  The increase in statistically significantly trends was 0.09%.  The increase insignificantly significant decreases was 0.03%.  These are essentially zero changes.

Nationally, there are more significant increases than decreases. Some regions, however have trends that go against these averages.  In southern Ontario, there are a few more decreases than increases, but twice as many statistically significant decreases than increases:


  • Decreasing annual maximum rainfall volumes over all durations 5 minutes - 24 hours   = 43.4%
  • Zero trend in annual maximum rainfall volumes over all durations 5 minutes - 24 hours =   4.3%
  • Increasing annual maximum rainfall volumes over all durations 5 minutes - 24 hours     = 42.1%
  • Number of statistically significant decreases = 12
  • Number of statistically significant increases = 6