Sunday, April 12, 2020

Are Summer/Winter Longer/Shorter Than They Used To Be?

Headline

A comparison of consecutive 30-year periods shows that summers in the U.S. and Canada are getting longer, and winters are getting shorter. The length of summer is about 6% to 10% longer in most regions. Winter is about 7% to 11% shorter in the Lower 48, and a staggering 30% shorter in Alaska. As temperatures continue to increase, expect these trends to continue.

Table 1. Changes in winter and summer length compared to 90-day reference period.

Introduction

Is summer longer than it used to be? Is Winter shorter than it used to be? To answer these questions, we first need to define what winter and summer are. Should we think of them as December-February  and June-August? If so, then winter and summer are exactly the same length every year. Of course this isn't what you were thinking.

What you really want to know is whether summer heat lasts for a longer period of time and if winter cold is shorter. The answer to these questions are an unambiguous yes for most places. The reason for this is simple, the climate is warming in most places. If the average temperature is warmer, then the comparison to what temperatures used to be like will change accordingly. Think of it this way, if you live in Omaha, Nebraska, and you imagine what summer is like (length and intensity) and then you move to Houston, Texas, you would experience a (much) longer period of summer conditions in Houston that what you are accustomed to. Similarly, if you moved from Chicago to Oklahoma City, you would say that you effectively shortened your winter. With a changing climate, we are effectively relocating our cities farther south.

Australia Study

In March 2020, the Australia Institute published a study titled Out of Season, which looked at this exact question. They asked if summer was getting longer and and winter was getting shorter by comparing similar period from two 20-year time spans. They noted a dramatic increase in the length of summer and a dramatic decrease in the length of winter. There are very important philosophical and methodological differences between the Australian study and the current study that will be noted at the end of this post.

Other Season Length Studies

There are many, many papers that discuss changes in the wet season, the dry season, the snow season, the frost-free season, and so on. Relatively little has been done on changing boreal seasons. The most interesting paper is a European study that looked at the changes in the length of summer over a 63-year period (Peña-Ortiz et al. 2015). The authors did a grid-based study and computed a detrended average of all the June daily temps for each grid cell. The 63-year average June temperature value was declared the unbiased start of summer. The same procedure was performed on September temps to determine an unbiased end of summer date. Next, the raw (untrended) grid cells were evaluated for each year and when a 30-day average daily temperature reached the reference start and end dates, they were flagged as the begin and end of summer for each year. With 63 start/stop summer values for each grid cell, a trend could then be computed.

A new study by Hekmatzadeh et al. (2020) looked for novel ways to assess changes in the summer and winter periods for two cities in Iran. They start by identifying the warmest and coldest 90-day periods of the year (using a 90-day smoothed average of daily temperatures) and define those as summer and winter respectively. For deciding when each summer/winter began/ended each year, I'll be honest, I cannot figure out for the life of me what the heck they did. What ever it was, it was very poorly explained. The result was a time series of begin and end dates for summer and winter in each year. They were then able to conduct linear regression trend analysis on the results. Also, they were able to assess the difference in the timing of the seasons for each year.

An earlier study by Yan et al. (2011) also looked for changes in the warmest and coldest 90-day periods of the year to assess changes in the warm and cold season lengths and intensities. Unlike the previous study, this one assess the changes in annual season begin and end dates for over 500 cities (stations) across China. An elaborate methodology is used remove the "noise" from daily observations. Both this study and the previous study systematically look at each year's temperatures and extract begin and end points of for the seasons from the data. You'll see below that our new study uses constructed climate normals – thus alleviating the problem of noisy daily data.

Methodology for This Study

To identify whether season lengths are changing, we need to define a modern period and a reference period. I decided to use consecutive 30-year periods (1990-2019 as the modern period and 1960-1989 as the reference period). Using the GHCN-M climate database, I identified all stations with at least 20 years of complete data in both time periods. There were 6,625 qualifying stations globally. In the U.S. and Canada, there were 3,250 qualifying stations. For each station, daily climate normals were computed using a 3rd-order (cubic) spline. This very closely approximates the official NCEI climate normals procedure.

For the reference period, the warmest 90-day period of the year and the coldest 90-day period of the year were identified and declared to be the baseline summer/winter periods respectively. We can then compare the climate normals of the new, modern time period and identify the dates where the old seasonal temperatures begin and end.

Examples of changing summer and winter temperatures: 

Imagine the warmest 90-day period of the year used to be June 3rd to August 31st and on both June 3rd and August 31st, the daily average temperature was 70°F (it's warmer during the intervening days). Now imagine it's 30 years later and the date where the summer temperature first reaches 70°F is May 30th and the date where the temperature drops back down to 70°F is September 5th. Compared to the earlier period, we now achieve summer heat 4 days earlier and it lingers 5 days longer. This gives us a 99-day period in today's climate that experiences the same length of warmth as the 90-day period of yesteryear – a 9 day increase. Two animation example of 5 stations are shown below. A summer animation and a winter animation. Remember that we are not comparing the intensity of the warmth/cold, just the length of time we experience comparable temperatures.

Figure 1. Changes in summer length for 5 U.S. stations.

Figure 2. Changes in winter length for 5 U.S. stations.

Summer Analysis

The vast majority of stations globally now experience a longer summer compared to the previous 30-year reference period. The exception to this rule in North America is parts of the Midwest and Great Plains. Areas in blue on the first map show where summer conditions are slightly shorter. For every place else, the closer you get to an ocean, the longer summer gets. This makes sense as the oceans have warmed dramatically and they impart a tremendous influence on the climate.

There is also a notable urban heat island (UHI) effect. Cities are experiencing longer summers than nearby rural areas. Remember that 80% of Americans live in urban areas. The added increase in urban heat is real and affects the lives of those 80% of Americans.

Figure 3. Change in the number of days in summer compared to prior reference period.

Winter Analysis

The change in the length of winter is even more dramatic than the summer changes. While average summer conditions last 7 days longer (97 days vs 90 days) than they used to, comparable winter conditions last 15 days less (75 days vs 90 days) than they used to. The winter patterns in the Lower 48 are broadly similar to the summer patterns, except the winter warming is slightly less stratified from north to south. In northern Canada and Alaska, the shortening of winter is dramatic. In fact, along the North Slope of Alaska, even the low point is winter during the current period is warmer than any of the days in the 90-day winter from 30 years prior! Urban heat island effects are equally as pronounced in the winter map as they are in the summer map.

Figure 4. Change in the number of days in winter compared to prior reference period.


Selected Stations

The graphic below shows how long the previous 90-day summer and winter are in today's warmer climate. This is only a partial list. A complete list can be made available upon request.

Table 2. Number days in winter and summer in most recent 30-year period compared to reference period for selected stations

Changes in Season Timing

Instead of looking at the length of the seasons, what if we just look to see the difference in the timing of the warmest and coldest 90-day periods from the consecutive 30-year periods (1960-1989 vs 1990-2019)? The maps below show the difference in the timings.

In summer, there is a pronounced shift toward earlier peak heating in Alaska, and a pronounced shift later in the northern Rockies. Outside those areas, the changes are for earlier summer heat in southerly latitudes and later summer heat in northerly latitudes.

For winter, the patterns are much less distinct. Most places are seeing peak cold occur sooner. More appropriately, late winter is warming faster. This effectively pushes the coldest part of the year to an earlier point on the calendar.

Figure 5. Change in timing for warmest 90-day period of the year.

Figure 6. Change in timing for coldest 90-day period of the year.

Differences With Australia Study

The Australia study noted earlier uses the following methodology.

1) Define the seasons strictly based on calendar months (Jun-Aug and Dec-Feb).

2) Pick two 20-year periods (1950-1969 and 1999-2018).

3) Use a 21-day average (smoothing) filter of daily temperature and construct a 20-year daily climatology.

4) Identify the 1950-1969 begin and end of season temperatures in the reference period and looks for those temperature start/stop points in the 1999-2018 modern period.

5) Compute season length changes for 70 stations south of 25°S latitude.

Comparison of Australian and Current Studies

1) The current study uses constructed daily normal temperatures from monthly data – the same technique used by the NCEI and the WMO. The Australia study uses smoothed daily data. The advantage of using constructed climate normals is that the smoothing is a feature of the spline, whereas the 21-day average of daily data tries to approximate a smoothed line. An argument can be made for either approach.

2) The Australia study sets summer and winter in the reference period to be matched with the calendar months (Jun 1/Aug 31 and Dec 1/Feb 28). The current study identifies the warmest/coldest 90-day periods regardless of how they match with the calendar months. This allows us to track the changes in timing of the seasons.

3) The Australia study uses two 20-year periods that have a 29-year intervening gap. The current study uses two consecutive 30-year periods. This is a non-trivial methodological difference. The annual temperature change in Australia between the 1950-1969 and 1999-2018 time periods (their methodology) was 0.755°C. The annual temperature change in Australia between the 1960-1989 and 1990-2019 time periods (our methodology) was 0.534°C. [Computed from Berkeley Earth global temperature data.]

Results Analysis

Using the Australia study's 20-year periods versus our 30-year periods results in a magnification of the warming by 41% (0.755°C vs 0.534°C). This large difference has a substantial impact on the changes in the length of summer and winter and is largely why they show a much more substantial lengthening of summer and shortening of winter.

The GHCN-M data set contain 215 stations in Australia that met out criteria. We performed the same analysis for Australia that we performed for the U.S. and Canada. In Australia, we determined that summer is now (1990-2019) 9 days longer than it used to be compared to the 1960-1989 reference period (99 days vs. 90 days). This is dramatically different that the 4-week lengthening of summer noted in the Australian study (118 days vs. 90 days). For the U.S. and Canada, the change in summer length was 7 days (97 days vs. 90 days).

For winter in Australia, we computed a decrease in winter length of 9 days in our two reference periods (81 days vs. 90 days). The Australia study indicated a decrease in winter length of 23 days (69 days vs. 92 days). For the U.S. and Canada, the change in winter length was 15 days (75 days vs. 90 days). Much of the U.S. and Canada decrease was a result of dramatic changes in Arctic latitudes.

The method of constructing daily averages vs daily normals, and the selection of reference and modern periods explains the majority of the differences between the two methods for Australia. One method is not necessarily better than the other, but it's important to understand why the results are so different.

Alaska-Centric Maps

These are the same maps show in in figures 3, 4, 5, and 6, but with a focus on Alaska.





Europe Maps

Here are the Europe versions of the same analysis. The modern summer length is now 9 days longer (99 days vs. 90 days). Winter is now 65.6 days compared to 90 days in the 1960-1989 reference period (24.4 days shorter). 



References

Hekmatzadeh, A.A., Kaboli, S. & Torabi Haghighi, A. New indices for assessing changes in seasons and in timing characteristics of air temperature. Theor Appl Climatol (2020). https://doi.org/10.1007/s00704-020-03156-w

Peña-Ortiz, C., D. Barriopedro, and R. García-Herrera, 2015: Multidecadal Variability of the Summer Length in Europe. J. Climate, 28, 5375–5388, https://doi.org/10.1175/JCLI-D-14-00429.1

Swann, Tom and Mark Ogge. 2020: Out of Season: Expanding summers and shrinking winters in subtropical and temperate Australia. The Australia Institute. https://www.tai.org.au/sites/default/files/P834%20Out%20of%20Season%20%5BWEB%5D.pdf

Yan, Z., Xia, J., Qian, C. et al. Changes in seasonal cycle and extremes in China during the period 1960–2008. Adv. Atmos. Sci. 28, 269–283 (2011). https://doi.org/10.1007/s00376-010-0006-3

Sunday, December 17, 2017

Christmas Climatology

The following is a list or random Christmas Climatology facts and figures. All data come from the GHCN-D database from NCEI.


A) No station outside of Hawaii has ever had a 10" rain event on Christmas Day. The Continental U.S. record is 9.84" at Dothan, AL, in 1964. LINK

B) Hawaii has seen four 10" rainfalls on Christmas Day. Three in 1927 on the Big Island. LINK

C) The wettest Christmas *may be* 1975 and the driest *may be* 1999. LINK


D) A closer look at the ESRL 20th Century Reanalysis data set (1851-2014) shows that Christmas 1889 was the warmest during that time period (also exceeding 2015). Note: this data set models temps using SLP, SST, and sea ice. LINK


E) The coldest Christmas is easily 1983. Christmas 1983 is not only the coldest Christmas Day on record. In the R1 Reanalysis database, Dec 25, 1983, is the second coldest of any day between Jan 1, 1948, and present [12/22/1989]. LINK1 LINK2



F) The coldest Christmas in Alaska was 1961.


G) The warmest Christmas in Alaska is a near tie between 1971 and 1985.


H) The lowest Christmas Day temperature in the Lower 48 was -53°F at Riverside, OR, in 1924. LINK 


I) La Pryor, TX, hit 93°F on Christmas Day 1955. That is the U.S. Christmas record. 

J) The lowest Christmas high temperature was -25°F at Wolf Point, MT, in 1983. LINK 


K) The lowest max (coldest high temperature) on an Alaska Christmas was -56°F. Allakaket (1917) and Eagle (1961) share the honor. LINK

L) The lowest low temperature on Christmas Day in Alaska was a chilly -66°F at Allakaket in 1954. LINK 


M) The warmest Christmas Day temperature in Alaska was 57°F at Copper Center School in 1962. LINK 

N) The greatest Christmas Day snow is 44.0" at the Mount Rainer Paradise Ranger Station in 2015. Note: This is possibly a three-day total. The next highest total is 40.2" at Portola, California, in 1971. LINK 


O) The deepest snow depth on Christmas Day is 160". Both Mt. Rainer Paradise Ranger Station (1996) and Mt. Baker Lodge (1948) achieved this value. LINK 

P) There are 4,469 stations with at least 50 years of Christmas Day temperature data. All but 21 (not incl Hawaii) have had at least one Christmas freeze. 7 in Florida, 13 in California, 1 in Louisiana. LINK

Q) Utqiaġvik (Barrow), Bettles, Northway, Tok, Kotzebue, Ft. Yukon, and Tanana, Alaska, have never had a Christmas Day temperature above freezing. [min 50 years]. LINK 

R) In Alaska, Tok (5°F), Northway (9°F), and Ft. Yukon (9°F) have never had a Christmas low temp warmer than 10°F. [min 50 years] LINK

S) In 1919, only 2.6% of stations in the Lower 48 had measurable precipitation on Christmas Day. In 1940, 48.0% of stations had measurable precipitation. LINK

T) There are seven station that have not recorded measurable precipitation on Christmas Day [min 50 years]. LINK

U) The Otis 2 NE Cooperative station in Oregon has recorded measurable precipitation on 53 of 65 Christmas Days. That is the highest percentage outside of Hawaii. LINK. They also have the longest current streak of Christmas' with measurable precipitation. 23 in a row and counting. Outside the Pacific NW, only Bradford, PA, has had 20 consecutive Christmas' with measurable precip (1961-1980). LINK

V) The Houghton Lake AP, Michigan, station once received measurable snow on 17 consecutive Christmas Days (1964-1980). LINK 

W) Map showing the record lowest Christmas Day temperature for stations with 40+ years of data. LINK


X) Map showing the warmest Christmas Day temperature on record using stations with at least 40 years of data. LINK


Y) Mould Bay, Canada, has Christmas Day data for 64 years. They have never recorded a Christmas temperature above 0°F.


Z) U.S. Stations with 10+ consecutive White Christmases overlaid on historical probability. Flagstaff, AZ, is a near certainty to end their run of 11 straight White Christmases. Doesn't look good for Wolf Canyon, NM, either. Every other dot looks safe. LINK 


AA) Coldest Christmas on record based on Reanalysis data: 1851-present. Note: pre-1948 methodology is less robust. LINK


AB) Historical chance of measurable snow on Christmas Day. LINK 


AC) Stations that have ever had a White Christmas. LINK





Friday, December 1, 2017

Defining the Seasons

What is a season? Well, if you look at a calendar, the seasons start on December 21, March 20, June 21, and September 22. These are more properly called astronomical seasons. Climatologists traditionally use whole calendar months to describe the seasons – December to February, March to May, June to August, and September to November. These are called climatological seasons. Most natural scientists use these month-based season definitions.

Season Definitions

Surprisingly, very little research has been done on using climatological data to fine tune the definition of the seasons at the local scale. When I looked a few years ago, I only found a single paper in the peer-review literature that specifically looked at reshuffling the dates where the seasons begin (citation pending). This effort only attempted to assess whether the 90-92 days seasons actually line up with the calendar months. They showed that it was actually not that far off.

More recently, Boustead et al. (2015) used an elaborate rubric to define the winter season using temperature, snowfall, and snow depth – the AWSSI. Their definition of winter was expansive and made sure to capture the maximum length of wintry condition. In March/April, a measurable snowfall extended the winter season until (at least) the day of the snow – and longer if it stayed on the ground. However, an argument can be made that multiple days in the 60°s/70°s during March that are followed by a quick snowfall does not mean those days in the 60°s/70°s are part of winter. The AWSSI bins them in the winter season. This is not a flaw of the AWSSI; as the AWSSI's goal is to capture all winter conditions.

The Data

I used the Global Historical Climatology Network version 4 (GHCNv4) database of monthly climate temperatures for all analysis. Here comes an important point. Climate normals are based on monthly temperatures. This seems counter intuitive. Why not use daily data if we have it? The answer is that daily data are chaotic. In addition, many stations collect data at irregular schedules that make daily estimates difficult but are good at the monthly level.

Up through the 1971-2010 climate period, the National Center for Environmental Information (NCEI), formerly the National Climate Data Center (NCDC), used a cubic spline fit of monthly average temperature to interpolate daily climate normals. In the 1981-2010 climate period, they modified the procedure somewhat using a methodology that is explained in some detail but in a way that is not replicatable.

For my analysis, I used 1981-2010 monthly temperature data and applied the cubic spline technique that NCEI used in prior climate normal periods. The daily values produced are not very different than the non-replicatable NCEI published values. With that caveat ...

Adjusting Cold 90-Days and Warm 92-Days

The December 1 to February 28 time period is 90 days long (I am ignoring Leap Days). Is this really the coldest 90 days of the year? Correspondingly, the June 1 to August 31 time period is 92 days long. Is this really the warmest 92 days of the year?

These are questions that have long interested me. To answer the question, I generated daily normal temperatures for every U.S./Canada station in the GHCN v4 data set (7,636 stations). For each of those station, I flagged the coldest 90 days of the year and the warmest 92 days of the year. The seasons are therefore redefined as:

1) Winter: coldest 90 days
2) Summer: warmest 92 days
3) Spring: days between winter and summer (undetermined length)
4) Fall: days between summer and winter (undetermined length)

The length of winter and summer are fixed and the combined length of spring and fall are fixed – but the length of spring and fall as individual seasons vary from place to place.

Figures 1-4 below show the dates of winter and fall, and the lengths of spring and fall using the aforementioned methodology. Figure 5 shows a sample of stations with the start and end dates of all seasons using a color-coded index.

Figure 1. Coldest 90-day period of he year during 1981-2010 using climate normals generated from the GHCN v4 data set.

Figure 2. Warmest 92-day period of he year during 1981-2010 using climate normals generated from the GHCN v4 data set.

Figure 3. The number of days between the coldest 90-day period and the warmest 92-day period. This is the length of spring. 

Figure 4. The number of days between the warmest 92-day period and the coldest 90-day period . This is the length of fall. 

Figure 5. Graphical representation of the begin/end dates for 63 selected cities in the U.S. using the coldest 90-day period, the warmest 92-day period, and the intervening periods. 

 Defining Seasons Using Annual Temperature Range

Instead of retaining the length of climatological seasons to mimic the length of calendar months, why not define some temperature thresholds for the warm and cold seasons and let the chips fall where they may? This is an idea the Rick Thoman with the National Weather Service Alaska Region came up with. He suggested that if you took the annual range of normal temperatures (highest minus lowest), those days that are in the top 1/4 of that range are summer days, those days in the lowest 1/4 of that range are winter days, and the intervening days are either spring or fall days.

This produces a much different distribution of season lengths. Most places "hover" near the warmest and coldest portions of the year for more than 90 or 92 days. For example, the annual maximum normal for Washington D.C. (Dulles) is 76.7°F. The annual minimum normal is 33.1°F. The range is therefore 43.6°F. Any days warmer than 65.8°F are considered summer and any days below 44.0°F are considered winter. The transitions between those periods is considered spring and fall. This yields a winter length of 114 days, a summer length of 119 days, a spring length of 69 days, and a fall length of 63 days. Note the dramatically longer lengths of summer and winter compared to the 90- and 92-day lengths from the previous section.

Because both the start date and the lengths of summer and winter are variable using this methodology, we cannot have a single figure (like Figures 1 & 2) that gives all the necessary information about those seasons; therefore, I just show the lengths of the four seasons in the map set below. Figures 6-9 below show the dates of winter and fall, and the lengths of spring and fall using the top/bottom temperature quartile methodology. Figure 10 shows a sample of stations with the start and end dates of all seasons using a color-coded index. It is the exact same set of stations that were shown in Figure 5 above.

Figure 6. Length of the winter season using the quartile methodology and based 1981-2010 using climate normals generated from the GHCN v4 data set.

Figure 7. Length of the summer season using the quartile methodology and based 1981-2010 using climate normals generated from the GHCN v4 data set.

Figure 8. Length of the spring season using the quartile methodology and based 1981-2010 using climate normals generated from the GHCN v4 data set.

Figure 9. Length of the fall season using the quartile methodology and based 1981-2010 using climate normals generated from the GHCN v4 data set.

Figure 10. Graphical representation of the begin/end dates for 63 selected cities in the U.S. using the quartile season definition methodology.











Thursday, September 28, 2017

Map Collection





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A) Temperature maps (percentiles, medians, and averages).

















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B) AWSSI









 


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C) Daylight & Twilight










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D) Record Consecutive Temp & Precip Days












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E) Wettest / Driest  Months & Seasons






















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F) Rick's Wet Season Index




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G) Holiday Climatology





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H) Eclipse Maps




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I) Precipitation Percentiles

















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J) Precipitation Recurrence Intervals








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K) Defining Seasons










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L) ESRL Rankings Website Output





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M) Days per Year Threshold Count







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N) First/Last Temperature Date





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O) Single Year/Season Analysis





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P) Snow Depth


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Q) Seasonal Midpoints





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R) Change Across Time Periods








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S) All-Time Extreme










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T) Severe Weather






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U) Random Stuff