Can We Use Daily Rainfall Models To Predict Short Duration Trends? No - Observed Daily and Short Duration Trends Diverge

One can assess trends in rainfall intensities over various durations and return periods using Environment Canada's Engineering Climate Datasets.  National trends based on updating 226 station IDF curves were shown in an earlier post.

What are the trends in regions of Canada that have experienced significant flooding in the past?  And do the trends projected by models for long durations (1 day precipitation) match observed data trends?  No - some 24-hour trends are decreasing despite models estimating they will go up (or have gone up because of increasing temperatures).

Also, what is happening with observed short duration intensities, the ones responsible for flooding in urban areas, compared to the observed 1-day trends?

The data show short duration and long duration trends diverge. Therefore relying on models of 1 day precipitation to estimate what is happening with short duration, sudden, extreme rainfall is unfounded.

A couple charts help illustrate these observed data trends and show what is wrong with relying on models to project local extreme rainfall.

This is the trend in observed rainfall for southern Ontario climate stations, using median changes in IDF statistics:

Southern Ontario Extreme Rainfall Trends
Long duration intensities are decreasing and short duration intensities are decreasing even more.  The extreme intensities (red dots = 100 year, orange dots = 50 year) decrease more than the small frequent storm intensities (green dots = 2 year).  Observed data diverges from Environment Canada models that suggest intensities are going up due to a warmer climate.

These are the trends for Alberta observed rainfall when new data is added in the v3.10 datasets:

Alberta Extreme Rainfall Trends
In Alberta, long duration intensities decrease significantly (100 year is down by 4% on average).  Meanwhile the short duration intensities increase.  The long duration decrease is contrary to Environment Canada's simulation models that estimate 1 day rainfall at a sub-continental scale.

In northern Ontario, trends are different than in southern Ontario as shown below:

Northern Ontario Extreme Rainfall Trends

In northern Ontario the long duration intensities have increased but short duration intensities have decreased.  So we see short and long duration rainfall trends are diverging when we consider new data.

Climate modellers suggest that simulated 1 day precipitation can guide what happens during short durations too.  Observed data suggest otherwise.  Trends diverge.

In brief, for this sample of regions shown above, we see these trends:

Location                 Short Duration Trend         Long Duration Trend

Southern Ontario      Larger Decrease                        Decrease
Northern Ontario            Decrease                              Increase
Alberta                            Increase                               Decrease

Remember "All models are wrong, some are useful".  Climate models do not accurately project changes in extreme rainfall in Canada based on observed data.  Furthermore, simulated 1 day precipitation trends from models cannot be used to assume short duration trends related to flooding in urban areas - short and long duration rainfall trends are observed to change in opposite directions in sample regions across Canada.

Super Models vs Dowdy Data - How Climate Models Diverge From Observations On Extreme Weather

A recent special article in the Financial Post noted the difference between models and observations on extreme rainfall: link

Recent reporting by CBC and Radio Canada International (RCI) have reported shifts in extreme rainfall frequency, stating that there is confirmation that a warmer climate is now making extreme rainfall more frequent and intense.  The confirmation, however, was from models analyzed by Environment Canada, and not actual measured rainfall.

As pointed out in the Financial Post article, both CBC and RCI confused models with actual observed data in stating broad confirmations.  They overlooked limitations in the models to represent local events and extreme events, omitted data that showed all the models were wrong in some regions (projected increasing rainfall when data showed decreasing rainfall), and failed to mention that other climate effects like less snow in a warmer climate can decrease flood risk, mitigating precipitation increases.

Fundamentally, observed rainfall frequencies and model frequencies are not consistent, despite RCI and CBC reporting.  The following tables show the clear difference between what models project could happen and what actual data show has happened.

This first table relates to the recent CBC and RCI reporting on a North American climate model.  The model predicts that 100 year storms become 20 year storms (i.e., for a given intensity), meaning more frequent.  Alternatively, the model says that intensities of a given frequency are higher.  In contrast, the observed data for Canada show a slight decrease in 100 year intensities at 226 climate stations, meaning storms of a given intensity are are not more frequent, but rather slightly less frequent when recent data are factored in.

Extreme Rainfall in Canada - Trends in Modelled vs Observed Data for 100 Year Storm

The second table below is for the 50 year return period storm - it shows projected model return period shifts of 50 to 35 years from model.  The results are averaged across Canada.  In comparison, 226 climate stations across Canada have observed that results in a slight decrease in 50 year storm intensities.  Like the 100 year storm above, that means actual storm frequencies are lower now.  Old 50 year return periods are now longer than 50 years now.  

Extreme Rainfall in Canada - Trends in Modelled vs Observed Data for 50 Year Storm
The CBC reported the above 50 to 35 year model shift as actually having already occurred in its In Our Backyard interactive: (see flooding tab)
The CBC claimed that intensities in Toronto are greater today, resulting in more flooding.

While it is challenging to draw conclusions from trends at individual climate stations, shifts at a couple of  Toronto climate stations are shown in the 100 year and 50 year tables as well to check the CBC reporting.  The Toronto Pearson International Airport and Toronto City (aka Bloor Street) gauges have very long records to compare old and new intensities.

The old Pearson 100 year 24-hour storm intensity (top table) is now a  417 year storm, meaning it occurs much less frequently now.  Alternatively, the magnitude of the 100 year storm intensity has dropped from past to present, meaning such storms are less severe.  This decline occurred despite that climate station recording the large July 8, 2013 storm.  The 50 year storm is now a 108 year storm, again less frequent than before.

Clearly local data at Pearson Airport, just outside of Toronto is not changing the same way that the Canadian model projections are.  Observed frequencies are longer, while the model estimated them to be shorter.

The Toronto City climate station shows only small changes in 24-hour storm frequency.  The 100 year frequency is slightly shorter at 97 year. Meanwhile the 50 year frequency is slightly longer at 52 year.  These changes are nominal and represent no significant overall change.  They are consistent with the average changes at 226 stations across Canada that also showed no appreciable change when 10 additional years of data were analyzed.  Across Canada, 100 year and 50 year rainfall intensities decreased slightly overall - the 100 year intensities decreased 0.5% and the 50 year intensities decreased 0.6%.

Clearly local data at Toronto City, essentially downtown Toronto, shows no change in extreme storm frequency or intensity, contrary to the CBS's reported model estimates.

To not rely on just a couple Toronto stations, one can look at at changes in intensities at all long term southern Ontario climate stations that have recent data updates.  Comparing the Engineering Climate Datasets v2.00 with data up to 2007 and v3.10 with data up to 2017 one can see a slight decrease in 50 year and 100 year 24-hour intensities, on average.  The stations and their lengths of record are shown below:

Southern Ontario Long Term Climate Stations with Recent IDF Updates (v2.00 to v3.10) - Environment Canada Engineering Climate Datasets
Overall, there are 978 station-years of data to analyze trends.

In southern Ontario the 100 year 24-hour intensities decreased by 1.0% while the 50 year intensities decreased by 0.9%, when additional data was added.  This suggests that the regional trends in Toronto per the Toronto City climate station, showing no overall change, are consistent with other stations in the region.  The southern Ontario data does not support the North American or Canadian model estimates reported by CBC and RCI that expect shorter return periods and higher intensities.

So beware of media reports that mix up models with actual observed data.


The following image expand on the tables above, showing where CBC and RCI made reference to the climate model results, and the text used to describe 'confirmation' of changes in rainfall.  Links to comparison charts (some that were in earlier posts) and tables are also included, showing the actual observed data trends and indicating Environment Canada source material.

Click to enlarge:

Comparison of 100 Year Return Period Rainfall Trends in Canada - Climate Models vs Observed Data, CBC and RCI Reporting

Comparison of 50 Year Return Period Rainfall Trends in Canada - Climate Models vs Observed Data, CBC Reporting 

How Have Rainfall Intensities Changed in Canada Over the Past 10 Year? Not Much. Extreme 100-Year Rainfall and Short Duration Intensities Causing Flooding Are Lower

Environment and Climate Change Canada's Engineering Climate Datasets including rainfall intensity duration frequency (IDF) statistics are regularly updated as observation records become longer, and more and more stations have sufficient data to analyze.

What do the recent updates show? There is no new normal in design rainfall intensities.  Over the past 10 years, the severity of extreme rainfall has decreased on average.

Short duration sudden rainfall rates responsible for flooding in urban areas have also decreased overall - only the frequent, low intensities show an overall increase, which can be expected given additional precipitation in Canada. Of course some regions may have different trends (a previous post has shown that the southern Ontario frequent intensities (i.e., 2-year return period) have decreased).

Where do design intensities, the statistics in IDF curves and tables, come from?

Annual maximum series (AMS) of recorded rain intensity are collected for duration intervals of 5 minutes to 24 hours.  These series are used to derive probability density functions to describe the frequency distribution of rainfall, and that can be used to determine specific 'return period' design intensities.  The return period is the inverse of the probability of a rainfall intensity (or volume) over a certain duration occurring during a given year.  So a 100-year intensity has a 1/100 or 1% chance of being exceeded each year, while a 2-year intensity has a 1/2 = 50% chance per year. Storm sewers are designed to convey 2, 5 to 10-year return period rain intensities - 5-year is most common.  Flooding, especially extreme flooding, occurs at higher return periods becoming more severe above the 25-year return period and increasing for 50 and 100-year intensities.

The recent version 3.10 update to IDF statistics analyzes rainfall data up to 2017.  These intensities can be compared to the version 2.00 datasets that included data up to 2007.  A total of 226 stations were analyzed to check for changes in intensity - this total includes about 72 stations that have been relocated, but by not more than 5 km from their previous location.  The same trends are apparent for all the exact match stations (92 stations) and stations with new IDs but unchanged coordinates (154 stations).

The following chart shows the ratio of new intensities to old intensities for these 226 stations, so 1.0 means no change in design intensities.

Extreme Rainfall Trends in Canada - Design Intensities by Duration and Return Period

What are the take-aways?

1) rainfall design intensities are generally unchanged over the past 10 years, considering 3313 station-years of additional data,

2) extreme rainfall intensities, the 100-year rates (red markers in the chart), have decreased - the shortest duration intensity governing urban flood risk has dropped the most,

3) short duration intensities that govern sewver design, 5-year return period intensities (purple markers) over 5-minute to 2 hour durations are unchanged on average,

4) 2-year intensities (green markers), the low intensity rainfall that is exceeded in 50% of years, has increased slightly - these intensities do not govern infrastructure design and are unrelated to urban flash flooding or flood damages.

Popular media has focused on theoretical changes in rainfall intensity, sometimes confusing those projections with actual changes in rainfall intensity that have been measured or observed.  See this review of recent CBC coverage in the Financial Post.  Increasing damage amounts are erroneously linked to changes in rainfall due to a changing climate.

If popular media were to focus on observed data, and actual trends in extreme rainfall statistics, like the trends reviewed above, it would have to temper claims of a new normal in extreme weather.  Data do not show increases the critical rainfall intensities - in fact, on average, extreme intensities have decreased.

Changes in v2.00 to v3.10 dataset intensities are shown in the tables below.

Rainfall Trends in Canada

The analysis above is based on assessing the effect of adding additional data to the v2.00 IDF data intensities.  It is also possible to assess the effects of new data by splitting the series into old and new halves to compare IDF intensities and look for trends.  The following charts show the change in two long-period climate stations in the Toronto area.   Rainfall volumes are shown for a 24 hour period - intensities would be simply the volumes divided by 24 hours.

Toronto Pearson International Airport Climate Station - Changes in 24 Hour Rainfall Frequencies

For the Toronto Pearson International Airport climate station, the return periods of the old period volumes (blue line) have shifted right in the new data set, meaning longer return periods for a given volume, i.e., lower frequency.

The chart also compares how a climate model has predicted return periods have changed from 1961 to 2010, covering approximately a similar period.  Those model frequency shifts were reported by the CBC (link: and considered a 1 degree warming scenario. The climate model predicts lower return periods for a given volume, meaning that volume occurs more frequently - that is not consistent with observed local data at this station that has shown significantly longer return periods in the new period.

Toronto City Climate Station - Changes in 24 Hour Rainfall Frequencies

For the Toronto City (downtown) climate station, the return periods of the old period volumes (blue line) have shifted slightly right in the new data set, meaning slightly longer return periods for a given volume, i.e., slightly lower frequency.

The chart again compares climate model return periods for 1961 to 2010.  Again, the model, which represent a large area, and not necessarily the specifics of the Toronto area predicts lower return periods for a given volume, meaning that volume occurs more frequently - that is not consistent with observed local data at this station that has shown no significant change.

It is possible to look at the change in intensity as opposed to the change in frequency.  The following chart for Toronto Pearson International Airport climate station presents the same data but expresses the changes in terms of intensity, as opposed to frequency.

Toronto Pearson International Airport Climate Station - Changes in 24 Hour Rainfall Volumes
Often you can read in media reports that both the frequency and intensity increased over time - this is a peculiar way to express changes as that data can be used to show a change in one or the other but realistically not both at the same time.  To show the change in frequency and the change in intensity would mean allocating the change in some proportion to the two.


Do we have enough weather stations to analyze trends in observations - yes! - we are getting more and more stations and data over time - see previous post regarding additional Environment Canada stations since 1990.

In addition, municipalities are adding 100's of stations to support local studies as described in another post. More rain intensity data than ever before.

Although the data shows less extreme rainfall in Canada, some confuse models that predict future conditions and measured data.  The CBC misinterpreted a model predicting that 50 year storms would happen every 35 years in a time period out to 2015, and reported that this projections has already happened - read more about that here.

Do We have Enough Climate Stations in Canada To Track Trends in Extreme Rainfall?

Some have suggested that we have lost so many climate stations due to cut backs in the 1990's that we can't accurately detect trends in extreme rainfall.  But many are confusing manual climate stations with the stations that collect rainfall intensity data, often automatically.  The number of stations measuring extreme rainfall has been increasing since 1990.

Declining number of stations was noted in the ECO's report 2018 GREENHOUSE GAS PROGRESS REPORT CLIMATE ACTION IN ONTARIO: WHAT'S NEXT? - (see Appendix D)

CBC New has also referred to this concept in responding to a complaint to the CBC Ombudsman regarding accuracy in reporting on extreme weather trends.  What has been cited as evidence of that decline is the chart in Appendix D in the ECO report above. CBC's Director of Journalistic Standards Paul Hambleton wrote:

"The report suggests several possible reasons for this inconsistency, including issues with data collection: There simply are not enough rain gauges. Rainfall data is collected using rain gauge buckets that can record both amount and intensity of rainfall. After a series of federal budget cuts in the 1990s, there are fewer rain gauge stations across the country than there were 60 years ago."

Fewer rain gauge stations? Or fewer "manual" rain gauge stations?  Yes there is a difference.

What does that chart show?  It summarizes declining manual stations in Canada and is a excerpt from the paper in Atmosphere-ocean An Overview of Surface-Based Precipitation Observations at Environment and Climate Change Canada (Mekis et al., 2018) -

The chart of manual station count in Canada is Figure 2a in the paper on the left below.
Number of Manual Climate Stations in Canada

This chart has been referred to in discussions on extreme rainfall trends.  For example, in the ECO report this chart has been related to intensity-duration-frequency of isolated localized storms as in the excerpt at right:

Readers of this blog will have seen extensive analysis of the trends in extreme rainfall across Canada, including annual maximum series and intensity-duration-frequency (IDF) trends.  The data used is that of Environment and Climate Change Canada, distributed in the Engineering Climate Datasets.

What do Engineering Climate Datasets show us in terms of number of stations that collect and analyze extreme rainfall and IDF trends - they have been increasing!  And the number of station-years of data has been increasing - that means more long-term data to support more reliable statistical analysis.  Good news. The following table summarizes the trends:

Rainfall Intensity Data in Canada
Number of Climate Stations in Canada With Rainfall Intensity Analysis

The newer datasets include more stations, a 22% increase in station count since 1990. And the number of station-years has increased by 48% since 1990 - that's almost 50% more data to analyze and derive IDF design curves since I graduated and started working in this field.

How have the number of stations with extreme rainfall analysis, increasing since 1990, compared to the number of manual stations decreasing since 1990? See chart below:

Climate stations in Canada - trends, count, type
Number of Climate Stations in Canada - Manual and Intensity-Duration-Frequency Stations.  Manual stations decreasing while IDF stations and number of station-years of data increasing. (note: v2.00 (557 stations) and v3.00 (596 stations) not shown on chart)

The Mekis et al. figure is shown in blue and the IDF station trends in orange. Obviously the decline in manual stations does not relate at all to the trends in IDF stations.  As noted in other blog posts, municipal IDF stations have also proliferated over past decades, complementing the IDF stations charted above.

So when CBC's Paul Hambleton writes: "After a series of federal budget cuts in the 1990s, there are fewer rain gauge stations across the country than there were 60 years ago" he missed an important detail - yes manual stations that are expensive to operate have declined, as we expect.  It makes sense that we have fewer manual climate stations since 1990. 
Technology changes.  A good summary of the changes in equipment is described by Mekis et al. - image above are from the website that describes the history of rain gauges and their evolution.

But what about automated weather stations? And what about the number of stations used to collect extreme rainfall information and rainfall intensities? Has the number of stations that define extreme rainfall decreased since 1990? No.

IDF stations have increased from 532 to 651 stations since 1990, many with longer periods of record - we have more extreme weather data to rely on today!  The CBC and others should clearly be more careful when interpreting data on climate station and extreme rainfall  monitoring.  

Yes, we're getting more extreme rainfall, and it's due to climate change, study confirms .. well not so fast

CBC News has a new report "Yes, we're getting more extreme rainfall, and it's due to climate change, study confirms"

The byline is "Federal scientists predict more frequent and severe rainfall in future", referring to this research paper Human influence has intensified extreme precipitation in North America by Megan C. Kirchmeier-Young and Xuebin Zhang

The research paper refers to "heavy rainfall", i.e., Kirchmeier-Young the lead author and research scientist at Environment and Climate Change Canada stated "We're finding that in North America, we have seen an increase in the frequency and severity of heavy rainfall events."

Kirchmeier-Young also refers to "extreme rainfall" and makes a connection to urban flooding in the CBC article:

"And as we continue to see warming, we will continue to see increases in the frequency and severity of extreme rainfall," Kirchmeier-Young said. "And heavy rainfall is one of the major factors in flash flooding, particularly in urban areas."

The CBC relates extreme weather to rising insured flood damage trends in Canada since the early 1980's.

Let's review:

1) What 'heavy rainfall' events were reviewed in Kirchmeier-Young's research paper?

2) Is 'heavy rainfall' for a climate researcher the same as 'extreme rainfall' for an engineer?

3) Do 'heavy rainfall' and precipitation trends follow 'extreme rainfall' trends used in engineering design?

4) Do 'heavy rainfall' events studied in the research paper cause damaging flood events, and flash flooding 'particularly in urban areas?

5) What are the trends in 'extreme rainfall' in Environment and Climate Change Canada's Engineering Climate Datasets, the data used by engineers to analyze and design infrastructure to manage flash flooding risks in urban areas?

6) What does Kirchmeier-Young's research paper reveal about previous extreme rainfall and flooding events in Canada - has climate change increased runoff that could aggravate flood damages?

1) What 'heavy rainfall' events were reviewed in Kirchmeier-Young's research paper?

The research paper abstract indicates "Here, we address the question of whether observed changes in annual maximum 1- and 5-d precipitation can be attributed to human influence on the climate."

What does "1- and 5-d precipitation" mean?  This is the amount of rainfall over one to five days, so 24 to 120 hours. While precipitation can include snowfall too, the focus is on rain.

Note, the research paper actually refers to 'heavy precipitation' and not 'heavy rainfall'.

The authors have confirmed that short-duration rainfall was not reviewed, only annual maximum daily rain.

2) Is 'heavy rainfall' for a climate researcher the same as 'extreme rainfall' for an engineer?


The research paper states:

"We focus on the annual maxima of 1-d (Rx1day) and 5-d (Rx5day) rainfall. Rx1day is important for flash floods as well as infrastructure design. Rx5day is relevant to large-scale river flooding."

A training session on the use of rainfall intensity design curves from a climate scientist (link: indicates that shorter times influence flooding (underline and all-caps emphasis are in the original material, not added here):

 "An urban centre could experience flooding from heavy rains falling over a SHORT period of time, such as A 5 TO 30 MINUTE PERIOD."

"• A rural highway with deep ditches on its shoulders would not likely be impacted by an intense rainfall lasting only 5 to 15 minutes, although the paved road itself would see ponding of water.
• A heavy rainfall event lasting 1 to 6 hours might be more significant for filling the ditches and overflowing the roadway."

So short durations are important for flooding.

From the insurance industry perspective, an Institute for Catastrophic Loss Reduction paper in Journal of Flood Risk Management notes the importance of short-duration rainfall (link: states

"Subdivisions built before the 1970s are less likely to be serviced by major systems (Watt et al., 2003), and are thus more vulnerable to overland flooding from extreme short-duration rainfall events."

A civil engineer will tell you that rarely that the a 1-day rainfall is not 'important for flash floods'.  Why? Because urban flooding is caused by short-duration rainfall.  Designers of storage facilities such as stormwater manage ponds may consider design rainfall events up to 24 hours.

In the Canadian Water Resources Journal, authors of Flood processes in Canada: Regional and special aspects (link: representing six universities across Canada, INRS-ete, and Environment Canada review "key processes that generate floods in Canada":

"Similarly, floods can be generated across most of the country by rainstorms with large depths and/
or intensities (Figure 1). Thus, convective and frontal systems can generate large short-duration rainfall intensities (Alila 2000) which can occur in all regions (Table 1). Nevertheless, the significance of such storms to flood generation varies across the country, with the greatest
depths and intensities for short-duration events in southern parts of Canada and the smallest in the Arctic. These short-duration events are often responsible for flood generation in relatively small drainage basins, given the greater chance of high-intensity rainfall occurring over
the entire basin (Watt et al. 1989)."

"Short-duration events are often responsible for flood generation".

"Small drainage basins" is equivalent to urban drainage systems. In the municipality where I was Manager, Stormwater our storm sewer drainage systems averaged just over 50 hectares in size.  Urban drainage systems that are 'flashy', responding quickly to rainfall running off hard surfaces, are characterized in engineering design by a 'time of concentration' that is the response time of the drainage area, and which is used to determine the extreme rainfall durations relevant to infrastructure design.  It is never 24 hours or one day.  Typical times of concentration are measured in minutes and up to hours.

The Ontario Ministry of Transportation describes the design rain storms that may be used to analyze rural and urban areas, including the duration of the storm (link:

Storms of duration up to 24 hours are applicable to rural land uses.  Storms of up to 4 hours (including flashy Chicago hyetograph temporal distributions) are applicable to urban areas.  The SWMM Knowledge Base, a discussion forum for the standard U.S.EPA Stormwater Management Model and other modelling platforms, provides insight into what storm durations practicing civil engineering / urban system modelling professionals use.  In the discussion thread "Design storm duration" (link: a duration of 24 hours is deemed by one practitioner to be 'ultra conservative' ("ultra conservative choice of a 24-hour storm but it hardly can be justified when no detention storage is involved"), another states that in small urban systems the 5-minute rainfall governs peak flows ("a small (25 acre) urban, very impervious, drainage area was that the peaks were almost the same no matter the duration, and that they were driven by the peak 5-minute rainfall"), and Ben Urbonas, Ben Urbonas,
President of Urban Watersheds Research Institute and Owner, Urban Watersheds, LLC (LinkedIn:  notes the use of durations of 2-6 hours ("All of our design storms are front loaded intensity types and range from 2-hour to 6-hour durations depending on watershed area.").

Marsalek and Watt's paper Design storms for urban drainage design in the Canadian Journal of Civil Engineering shows design storm durations of often 1 hour duration, sometimes up to 6 hours (US Soil Conservation Service (SCS) for rural areas, as highlighted in their Figure 1.

Marsalek and Watt tablulate design storms with duration and categorize the use of the storms for different hydrological studies, including urban/sewer design and other applications, such as the study of large rural basins. Table 2 from their urban drainage review shows durations of up to 1- 12 hours for Canada's Atmospheric Environment Service's (AES) storm, and 1, 3 and 4 hour storms for sewer sizing in other jurisdictions (see highlights below).

Practitioners in Ontario, Canada will know that longer duration storms are considered for large regional wastewater systems that have a slow response to long-high volume storm events.  These govern large trunk sewer system performance, but not local sewer system performance that is dominated by short duration rainfall.  Even small wastewater system trunks may be governed by short duration rainfall intensities where there are direct inflows, which is common for many flood prone systems.  Analysis of trunk system response in the Kitchener-Waterloo Region showed wastewater trunk peaks flows for most-highly correlated to the 5-minutes rainfall intensities in on Master Plan study (i.e., more than longer durations).

Rivard's paper in the Journal of Water Management Modelling entitled Design Storm Events for Urban Drainage Based on Historical Rainfall Data: a Conceptual Framework for a Logical Approach (link: summarize early work on characterizing storms in Canada and in the highlighted excerpt notes that 1- 12 hour durations represented convective (thunderstorm) and synoptic scale events. See the highlight to the right.

Rivard also summarized what storm durations are of interest for urban design graphically as follows:

So in small to medium basin, up to a 3 hour duration is critical, and for a very large urban basin, up to 6 hours.  Twenty four hour durations and longer are critical to large rural basins.

The statement "Rx1day is important for flash floods as well as infrastructure design." is therefore inconsistent with professional engineering practice in Canada.

Environment and Climate Change Canada publishes Engineering Climate Datasets including Intensity-Duration-Frequency statistics describing rainfall, both common, moderate and extreme, used from infrastructure design.  The durations analyzed are from 5-minutes to 24-hours.

So again, no, 'heavy rainfall' in a climate research paper is not the same as 'extreme rainfall' an engineer uses for infrastructure analysis and design. Rainfall over 1-5 days periods is not the same as extreme rainfall over minutes to hours used to design conveyance systems in urban areas - those 'flashy' systems with short 'time of concentration' characteristics.

The statement in the research paper "Rx1day is important for flash floods as well as infrastructure design." is questionable.  One-day rainfall is way at the fringe of influence on flash flooding.

3) Do 'heavy rainfall' and precipitation trends follow 'extreme rainfall' trends used in engineering design?

Kirchmeier-Young's research found that 1-day duration simulated precipitation from various models has increased over past decades, and this trend follows observations from HadEX2 (a global gridded dataset).

We can compare the HadEX2 trends across North America, and subregions shown in the research paper, with extreme rainfall trends based on Canadian climate station observations.  Let's start with the 1-day, 24-hour annual maximum rainfall trends across Canada.

The chart below shows how annual maximum rainfall has changed according to Environment and Climate Change Canada's version 3.10 Engineering Climate Datasets for all storm durations from 5-minutes to 24-hours.

For 24-hour durations, 4.9% of all stations have a significant increase, 91.2% have no significant change, 2.3% have significant decreases and 1.5% of stations had no data.

Comparing to earlier datasets:

                                                     Version 2.30           Version 3.00            Version 3.10

No significant 24-hour trend            91.5%                    91.1%                         91.2%

Significant 24-hour increase              5.3%                      5.4%                           4.9%           

So the percentage of data that has no significant trend is relatively steady, and represents over 90% of the data. The percentage of data that has a significant increase in 24-hour rainfall is decreasing relative to the earlier datasets.

Canadian Engineering Climate Dataset trend data does not show increases consistent with the research paper.

4) Do 'heavy rainfall' events studied in the research paper cause damaging flood events, and flash flooding 'particularly in urban areas?

No.  Flash flooding is due to short duration, high-intensity rainfall.

The severe thunderstorms that are responsible for urban flooding and that occur over minutes to hours are different than the storms that occur over hours to days as indicated in the RSI IDF training presentation noted above:

For this reason, those interested in turban flooding drivers should look at short duration rainfall extremes - see below.

5) What are the trends in 'extreme rainfall' in Environment and Climate Change Canada's Engineering Climate Datasets, the data used by engineers to analyze and design infrastructure to manage flash flooding risks in urban areas?

Short duration rainfall is responsible for urban flash flooding.  Environment and Climate Change Canada's Engineering Climate Datasets indicate the following on annual maximum rainfall trends across Canada:

The short durations from minutes to a couple hours have low percentages of significant increase, just like the 24-hour data noted above.  The amount of significant increases expected due to chance is 2.5% increasing and 2.5% decreasing.

In a review of an earlier dataset by Environment Canada's Shephard et. al in 2014 (link: these amounts of changes were deemed not significant:

"Based on this IDF single station analysis, and the more general single station climate results from the 1965–2005 period presented in Section 4a, we conclude that the annual maximum short duration rainfall values across Canada typically do not show a significant trend."

And more recently in Canada’s Changing Climate Report, such changes in short duration extreme precipitation were explained by chance (link:

"There do not appear to be detectable trends in short-duration extreme precipitation in Canada for the country as a whole based on available station data. More stations have experienced an increase than a decrease in the highest amount of one-day rainfall each year, but the direction of trends is rather random over space. Some stations show significant trends, but the number of sites that had significant trends is not more than what one would expect from chance (Shephard et al., 2014; Mekis et al., 2015; Vincent et al., 2018)."

The short duration intensities used for infrastructure design, derived based on annual maximum series, have not increased in many regions based on compiled studies (see previous post:  A review of design intensities in southern Ontario shows overall increases in short duration values (see previous post:

So no change in how infrastructure is designed based on short-duration design intensities (that is, not including checks or 'stress tests' for future changes).

6) What does Kirchmeier-Young's research paper reveal about previous extreme rainfall and flooding events in Canada - has climate change increased runoff that could aggravate flood damages?

Nothing.  The storms that lead to widespread urban flooding are not addressed in the research paper.  The processes driving 1-5 day rainfall are different than those driving short-duration rainfall.  There are no significant increases in the short-duration rainfall that causes flooding based on Engineering Climate Datasets as shown above.

Why then have damages increased over decades? Possible reasons are:

a) growth in net written premiums: more insured properties = more losses

b) urbanization: more pavement means more runoff and impacts

The landmark case Scarborough Golf Country Club Ltd v City of Scarborough et al. (Ontario Court of Appeal, 1988, decision indicates that Toronto-area urbanization markedly increased runoff stresses that caused runoff, erosion and flooding:

“Expert evidence confirmed the effect of the city's rapid urbanization and water control plans on the creek.”

“It is important to note that the case is not presented primarily as a complaint against flooding but
rather that the markedly increased flows and increased velocity of flow have caused and continue to
cause damage to the creek bed and the adjacent tableland.” and

“There can be no doubt that the storm sewer facilities and urbanization of the lands to the north of the Club are the cause of the effects just described and that the difference in flow and velocity of flow is very substantial.”

Cities are growing and there is more runoff as shown here in some regions:

Urbanization and Flood Risks

c) inconsistent data: the data source for losses cited by CBC changed from 2008 onward

Changing data methods can lead to different results (see previous post on this:


The research paper makes a reference to an attribution study for the 2013 Alberta flood.  It states:

"Additionally, event attribution studies have identified an increased probability of some individual extreme precipitation events in this region due to anthropogenic influence (4, 5)"

Reference 4 is:

B. Teufel et al., Investigation of the 2013 Alberta flood from weather and climate
perspectives. Clim. Dynam. 48, 2881–2899 (2017). (link:

So we have one Canadian storm assessed. Findings are:

"Event attribution analysis suggests that greenhouse gas increases may have increased 1-day and 3-day return levels of May–June precipitation with respect to pre-industrial climate conditions. However, no anthropogenic influence can be detected for 1-day and 3-day surface runoff, as increases in extreme precipitation in the present-day climate are offset by decreased snow cover and lower frozen water content in soils during the May–June transition months, compared to pre-industrial climate."

So greenhouse gases may have increased precipitation, but that is offset by less snow, resulting in no change in runoff, compared to pre-industrial climate.

So with no change in runoff, can there be a change in flood damages attributed to the precipitation change?  The net effect is no increase in risk.


To wrap it up, CBC has relied on a research paper that looks at rainfall events (1-5 day precipitation) that are not related to urban flash flooding and are not related to the events that lead to significant damages (convective thunderstorms with peak intensities over minutes to hours).  The research does not review short-duration rainfall that is relevant to infrastructure design governed by short 'times of concentration' - i.e., they are 'flashy'.  The research does not appear to be consistent with trends in 24-hour annual maximum rainfall observed at Canadian climate stations and as published in Environment and Climate Change Canada's Engineering Climate Datasets - data show few statistically significant increases and the percentage of significant increases is decreasing slightly for 24-hour rainfall across Canada.  The short-duration rainfall intensities responsible for urban flooding show no consistent changes, and any significant changes are explained by chance, according to Environment Canada.

Many factors go into increasing flood damages.  Changes in rainfall does not appear to be one of those factors.  Media should take the time to dive deeper into the technical details they reference to improve the accuracy of reporting, so that the public is better informed about complex issues.
Urban flooding is a complex issue, and an important challenge to address that requires significant funding and attention.  A better understanding of the causes of flooding, and any changes in design rainfall, is required to mitigate flooding in the most objective, cost-effective manner.  CBC has relied more on model predictions than on actual data in the past, even confusing the two (see previous post:  In this recent report it has not met its JSP principle for accuracy by confusing longer-term precipitation and short-duration extreme rainfall.


BONUS - Trends in short-duration rainfall, based on annual maximum observations, from Environment Canada's version 3.10 Engineering Climate Datasets are summarized below (link:  These tables consider stations with a long period of record and recently updated data for regions across Canada.

What COVID-19 Taught Us About Observed Data vs. Model Projections: They Are Different - Let's Remember That When Interpreting Climate Models

COVID-19 data vs models climate change projections model uncertainty
COVID-19 - observed data on ICU cases and projected capacity
"All models are wrong, some are useful".  Predicting COVID-19 conditions has taught us that models come with a great deal of uncertainty, and are based on a lot of assumptions.  Furthermore, models have to be constantly updated over time with real observed baseline data to represent the starting point for future predictions. At least we recognize the difference between theoretical model projections and the past observations on COVID-19 conditions.  More attention should be given to the difference between theoretical models of climate effects and observed changes in extreme weather.

In early April, COVID-19 ICU cases were projected to increase to 1200 in a best case to about 1500 in a worst case in Ontario, increasing considerably from actual data counts in late March.  The chart at right shows that ICU beds peaked at under 300 cases by mid April, a fraction of the best case model prediction, and has declined since.  So model projections should be viewed with some caution, and the reliability of the projections should be questioned and validated where possible with real data.

Predicting future weather extremes due to climate change effects has a great deal of uncertainty as well.  The recurrence time of extreme rainfall is predicted to decrease due to climate change effects, meaning that the "return period" of storms would become smaller.  For example, a rainfall event that had a return period of 35 years today (meaning a probability of occurring in any year of 1/35, or 1 in 35) has been predicted to occur every 12 years in the future (i.e., a higher probability of happening each year of 1/12 or 1 in 12 ... that a greater chance than today's 1/35).  That is what is projected to occur in Canada from now to 2100.

The above example on decreasing recurrence times is from a simulation presented in Canada's Changing Climate Report by Environment Canada (link:  It is for a future scenario with several assumptions about growth and emissions called the RCP8.5 scenario, representing a Representative Concentration Pathway of just one of several future scenarios.  The shift in 24-hour precipitation recurrence times are presented on Figure 4.20 b shown below:

Canada's Changing Climate Report Extreme Precipitation Return Period Recurrence Times RCP8.5 Model Simulations
Canada's Changing Climate Report Figures 4.20 b), Projected Extreme Precipitation Recurrence Time / Return Periods for Past, Present and Future Time Periods, RCP8.5 Model Simulation Scenario

As annotated above, today's recurrence time is noted as 35 years, the future recurrence time is 12 years and the past time was 50 years. So the model predicts these shifts in recurrence time (return period) and annual probability:

   Period         Recurrence Time       Probability Each Year
1986-2005             50 years                       2.0 %   (1/50)
2016-2035             35 years                       2.9 %   (1/35)
2081-2100             12 years                       8.3 %   (1/12)

Some have misinterpreted the theoretical, simulation model changes from past to present as 'actual' observed changes in extreme precipitation when in fact the Environment Canada report clearly notes these are 'projected changes' and are 'simulated by Earth system models' for the scenario RCP8.5.  A different scenario's simulated results, with different assumed emissions and growth, and different recurrence time shifts are presented in Figure 4.20 a) as well.

CBC News In Our Backyard Extreme Rainfall Trends
CBC News In Our Backyard - Flooding
CBC's In Our Backyard interactive notes "Climate change is no longer theoretical. It’s in our backyard" - unfortunately it presents theoretical past model trends as real changes that are "In Our Backyard" now.  Here is the online report link:

CBC News report: "Climate change is making extreme rainfall a more frequent occurrence. Storms that historically happened only once every 50 years are now coming every 35 years or less. By the end of the century, they could happen once every 12 years on average, according to a recent climate report from Environment Canada. All this increases the potential for urban flooding."

CBC News Past Present and Future Rainfall Recurrence Time Return Periods for for Severe Storms
CBC News In Out Backyard Extreme Rainfall Frequency - Past, Present, and Future Recurrence Times Confuses Simulation Model Projections With Observed, Historical Trends

So while predicted changes are only theoretical, CBC News mistakenly reports that changes have already occurred and are 'now coming' at smaller recurrence intervals (i.e., higher frequency and higher probability each year).

The CBC Ombudsman has indicated that the CBC should be careful to distinguish between past, present and future extreme rainfall trends, as noted in a recent post:

We agree.

A review of historical extreme rainfall trends in one region of Canada affected by may flooding events has shown no decrease in the recurrence time, or return period, of extreme precipitation.  A previous post showed that today's 35 year storms are actually occurring less frequently than in the past. In southern Ontario, long term climate station observations show that the average 25 to 50 year rainfall intensities today are actually slightly smaller than they were considering observations up to 1990. See previous post:

Analysis of the Version 3.10 Engineering Climate Datasets IDF Files updated in March 2020 show that southern Ontario long term rainfall intensities have decreased slightly since 1990, on average by 0.1%.  The 50 year return period rainfall intensities are on average unchanged.

If 50 year rainfall intensities actually occurred more frequently and now occur at a 35 year return period, as CBC mistakenly reported, then the magnitude of the 50 year intensities would have had to increase by about 6%.  This considers the example long term climate station at Toronto's Pearson International Airport - the 35 year 24-hour rainfall intensity of 99.7 mm at the airport would have to increase to the 50 year intensity of 105.7 mm.  Back in 1990, the 50 year 24-hour rainfall intensity at the airport was 109.3 mm, meaning the 50 year rainfall has decreased by several percentage points.  Here are the 1990 data (copied from my top desk drawer):

Toronto Extreme Precipitation Trends Climate Change Effects on Rainfall Intensity
Toronto Pearson International Airport IDF Table With Data Up to 1990 - 50 year design rainfall intensity of 109.3 mm  (shown here) was higher than today's version 3.10 Engineering Climate Datasets intensity of 105.7 mm (see table below to 2017).  

Here are the recently updated IDF values from Environment Canada considering data up to 2017:
Toronto Extreme Precipitation Trends Climate Change Effects on Rainfall Intensity
Toronto Pearson International Airport IDF Table With Data Up to 2017 - 50 year design rainfall intensity of 109.3 mm (see previous table to 1990) shown is lower than today's version 3.10 Engineering Climate Datasets intensity of 105.7 mm (shown here).

Climate models that predict more frequent future rainfall intensities, characterized by shorter recurrence times (i.e., lower return periods = higher probabilities of occurrence) are not necessarily in step with observations (see Toronto airport example above and previous post on southern Ontario long term stations).  Here is a comparison of past trends in 100-year rainfall intensity based on observed data and projections from various studies - the actual data curve is already 'flat', so the need to flatten the curve can only be made based on projections and not past data.
COVID-19 and Climate Change Effects on Extreme Weather Data vs Models and Uncertainty
Extreme Rainfall IDF Trends - Toronto 24-Hour 100-Year Rainfall Volumes per Environment Canada Engineering Climate Datasets - Past Data and Linearly Projected Trends Shown in Black.  Various Studies and Models Project Significant Increases That Have Not Shown Up In The Data Observed Data Statistics
Just like COVID-19 models have considerable uncertainty and must rely on observational data to calibrate and validate them - so they they are more reliable and useful in making projections of the future - climate models require checks on accuracy and usefulness.  Media like CBC News may not discern between model predictions and actual trend data which can mischaracterize trends in extreme weather.  Since models predicting extreme rainfall do not appear to match past observations over the recent past few decades, the accuracy and reliability to project conditions over the next 80 years should be closely scutinized.

While in the case of COVID-19, the need for "flattening the curve" is clear given the close scrutiny of observed data that has shown rising counts of infections, hospitalizations or deaths - that gives clear direction on actions to be taken to mitigate observed phenomena.  In the case of COVID-19, these values may even increase at an exponential rate.  In contrast, the IDF curve trends are largely flat if not already declining based on observed data in some regions.  Any change in extreme rainfall trends has been explained by natural variations (i.e., trends can go up).


There is a long-standing gap in the media mixing up predictions of extreme weather and actual Environment Canada observed data trends - sometimes a single report can start a narrative that can go unchecked for some time.  The "Telling the Weather Story" report is one such example where a theoretical shift in extreme weather has been reported, and repeated endlessly in the media as actual data when it is clearly not: