Saturday, February 28, 2015

Lowest Wind Chills in Winter 2014-2015

No matter where you live. it probably felt really, really cold at some point this winter. But the question is, how cold did it feel? There is a very straightforward way to assess this. There are several thousand Automated Surface Observing Stations (ASOS) across the U.S. that record a wide range of meteorological conditions every hour of the day (sometimes more frequently). To compute a wind chill value, all we need are the temperature and wind speed values. The good folks at Iowa State generously provide an archive of all ASOS observations and some tools to extract the data (thank you Daryl Herzmann!).

There are 2,242 ASOS stations with sufficient data to generate a meaningful map. Figure 1 shows all of the stations and color codes them based on (generally) 10°F categories of wind chill. Wow! Look at the extremely low wind chills experienced by the vast majority of U.S. residents. Over 70% of the U.S. had a wind chill below 0°F at some point this winter. The "winner" was the Mount Washington Observatory with a low wind chill of -87°F! For non–mountain top stations, Deadhorse, Alaska, came in with a low wind chill of -86°F. In the contiguous U.S., Pinedale and Laramie, Wyoming, had the low (non–mountain top) value at -55°F. A word of caution though. Sometimes bad values are reported by the ASOS. Therefore, some readings may not be accurate. (Note: to read about a -100°F wind chill, see this blog post).

Figure 1. Lowest wind chill at all ASOS stations during this winter (2014-2015). Al stations are shown as dots.

Showing a bunch of dots on a map isn't always easy on the eyes. Therefore, we can use a little computational magic to turn those dots into a continuous color scheme. To do this, I used ArcGIS's inverse distance weighted surfacing function to make the map shown in Figure 2.

Figure 2. Lowest wind chill during this winter (2014-2015). Colors derived from inverse distance weighted surfacing algorithm using all 2,242 ASOS stations.

The surfacing technique looks at a series of points to determine natural boundaries. This is often referred to as a "smoothing" technique. Dots from Figure 1 do not always line up with the color bands in Figure 2. This is a necessary compromise to make a map that is not too chaotic. Imagine five nearby stations with four stations having values in the mid -20°s and one station with a value of -30°F. The dots (see Figure 1) will reflect the true values but the all five stations will be assigned to the -20°s category in Figure 2 since those color bands are based on weighted values of a station and their neighbors.

In Figure 2, the mean grid cell value for the entire U.S. was -17°F. For Alaska, the average lowest wind chill value was -43°F and for the contiguous U.S. it was -12°F!

Selected Values

With over 2,000 values in the data set, there are too many to list in a table. However,this table has some selected low wind chill values for major airports around the U.S.


Table 1. List of lowest wind chill values at selected major airports around the U.S. during this winter (2014-2015).


** Supplemental Figure **

For reference, this map (Figure S1) shows the lowest observed air temperature based on daily climate reports for all stations in the U.S.
Figure S1. Lowest observed actual air temperature this winter. Data obtained through xmACIS2.

Monday, February 23, 2015

Climatology of 2015 Iditarod Route

Due to poor snow conditions in the southern mainland, the Iditarod race start was moved from Willow to Fairbanks. This is the second time in history (1973-2014) that the race start was moved due to low snow in the southern portion of the route. The other year that the race start was moved to Fairbanks was in 2003. The official restart will occur on Monday, March 9th. Approximately half way through the race, the 2015 route will join with the traditional northern route at the Koyukon village of Ruby. A map of the 2015 route is shown in Figure 1.


Figure 1. Iditarod route in 2015. Populated places along the route are shown as yellow circles.

Analysis Period

What does climatology tell us about the expected conditions during this year's Iditarod? To answer that question, we need to select an analysis period. In the last 20 years, the winning time for the Iditarod is 9 days, 7 hours, and 28 minutes. The top tier of mushers usually finish in about 10 days. Therefore, I chose a time period of 10 days for my analysis. Since the start date this year is on March 9th, the time period for climatological analysis is March 9th to March 18th. This brings up an important point. The analysis in this post is not a climate analysis of past Iditarods. Previous races usually began on a Sunday and the calendar date differs from year to year. This analysis is looking at the same time period over a number of years to assess what the range of temperature and snow conditions have been like along the route used in 2015.

Stations

There are eleven stations along the 2015 route in the Global Historical Climatology Network (GHCN) database. In this analysis I have restricted the date range to the 1973-2014 time period. This corresponds exactly to the years in which the Iditarod race has occurred. That gives us 42 possible years of data. Some stations, like Fairbanks and Nome, have outstanding data for all 42 years. Other stations have incomplete or interrupted data. A map of the climate stations used in this analysis is shown in Figure 2.



Figure 2. Climate stations along the 2015 Iditarod route.

Temperatures

When assessing the temperatures on a yearly basis, I used an average of all stations for all 10 days of the analysis period. This yields a single temperature value for each year. Since the stations are fairly well distributed geographically, arithmetic averaging is sufficient.

As you can see in Figure 3, a wide range of temperatures have been observed since 1973. Keep in mind that these are average daily temperatures (high plus low divided by two). Four years have seen an average temperature of 20°F or warmer and seven years have seen an average temperature below 0°F. Interestingly, the years since 2000 have been, on average, a little cooler than the years in the 1970's and 1980's. Based on climatology, it is reasonable to expect temperatures to average between +10°F and -10°F.

A note of caution, do not over interpret the trend in Figure 3. Remember that this year's Yukon Quest happened to take place during a brutally cold week during one of the warmest winters on record.


Figure 3. Average temperature for the March 9 to March 18 time period for the 11 stations along the 2015 route shown in Figure 2.

Now that we have seen the annual temperature chart, let's look and see how the warmest and coldest years varied on a day-to-day basis during the March 9 to March 18 time period. Figure 4 shows the three warmest and three coldest years.


Figure 3. Average temperature for the March 9 to March 18 time period for the three warmest and the three coldest years along the 2015 route shown in Figure 2.

Even in the very warmest years, only the last day or two was above freezing – even then only by a couple of degrees. The coldest years were quite cold. While not even close to this year's Yukon Quest, temperatures have average as low as -25°F (1995) with average low temperatures near -40°C/F. Keep in mind that temperatures on the river ice can be 10°F colder than at the climate stations.

On a broader scale, we can look at temperatures on a statewide basis using the ESRL Reanalysis tool. I put together a video of temperatures from March 9 to March 18 for each year between 1948 and 2014. Video 1 shows the time lapse of the temperature departures from normal from year to year.



Video 1. Temperature departure from normal from 1948 to 2014 during the March 9 to March 18 time period. The 1981-2010 climate normals are used as the temperature baseline.

Snow

What does a musher really care about? Snow, of course. How has the snow been during the last 42 years along the 2015 route? The short answer is that it has been consistently good. Figure 3 shows the average snow depth and average new snow for all stations along the 2015 route during the 1973-2014 time period.


Figure 4. Average new snow and snow depth for the March 9 to March 18 time period between 1973 and 2014 along the 2015 route shown in Figure 2.

The average snow depth was 20.8" and the lowest was still 9" (1986). Six years have seen over 30" of snow on average with a peak of 42" in 2009. As for new snow, most years have recorded 2"-5" of new snow during the 10-day period – average is 2.4".

Conclusion

While there are no guarantees in life, history tells us that the route chosen for the 2015 Iditarod is consistently cold and consistently snowy. Mush on!

Wednesday, February 18, 2015

Forgotten Earthquake of October 1922

An interesting item showed up when looking through some old Anchorage climate forms. Back in October 1922, a notation was made by the Anchorage climate observer that read, "Violent earthquake 7:29 p.m. One & 1/2 minute! 2 shocks." Figure 1 shows the scanned form for October 1922.


Figure 1. October 1922 climate form for Anchorage, Alaska.

Since I had never heard of this earthquake before, I decided to look around a little to see what turned up. A search of the USGS earthquake database showed no events around that time. A search of the Alaska Earthquake Information Center database also came up empty. A cursory search of the Alaska Division of Geological and Geophisical Surveys did not find and reports or listings for an earthquake in 1922 (note: I did not read through any reports).

Having struck out with the go-to earthquake centers, I went back to NCDC and pulled more reports. It turns out that this event was noted at several other stations. Figure 2 shows the Local Climate Data report for October 1922 in Alaska.



Figure 2. Portion of October 1922 climatological summary for Alaska (p. 75).

Using the list from Figure 2 as a starting point, here are the stations within 350 miles of Anchorage and their notations for October 5, 1922:

   Seward --> 7:30 p.m. Severe earthquake on 5th
   Matanuska Exp. Farm --> Distant Earthquake at 7:27 p.m. on 5th
   Chitina --> Earthquake 8:10 p.m.
   Paxon --> Slight quake 7:30 p.m.
   Iliamna AP --> Earthquake 9:00 p.m. Intensity (illegible)
   Kodiak --> (nothing)
   Talkeetna --> (nothing)
   Dillingham AP --> (nothing)
   Valdez --> (nothing)
   Cordova --> (nothing)
   Yakutat --> (nothing)
   Chickaloon --> (nothing)
   Kennecott --> (nothing)
   Copper Center --> (nothing)
   Healy --> (nothing)
   Nenana --> (nothing)
   Fairbanks --> (nothing)

Of particular interest was the notation for Seward: "Severe earthquake on 5th." Figure 3 shows the Seward form for October 1922 and Figure 4 shows a map of the stations that "felt" the earthquake.


Figure 3. October 1922 climate form for Seward, Alaska.


Figure 4. Map showing all stations that noted the October 5, 1922, earthquake on Cooperative Observer (COOP) form.


While the terms severe and violent are quite subjective, they certainly indicated a level of shaking beyond the typical Alaska earthquake. On my way home I stopped by the UAA Consortium Library to look at old newspapers and see if there were stories about the earthquake. The Anchorage Daily Times from that time period was quite disappointing. Not only was there no story about the earthquake but there were no local stories at all – only national stories. The Fairbanks News Miner was a much better newspaper then the Anchorage Daily Times but it too did not contain any stories about the earthquake However, the Seward Gateway did have a news story about the earthquake (see Figure 5). 



Figure 5. October 6, 1922, edition of the Seward Gateway.

Where was it centered?

The newspaper noted the length of shaking at 0:28. The Anchorage climate form noted the shaking was 1:30. What does that tell us? Some references note that shaking is more intense and of shorter duration close to the epicenter. Other references say that a stronger quake will be felt longer near the epicenter. Who is right? I am not a seismologist and cannot speculate. However, given the statement that it felt like it moved from northwest to southeast, and given the fact that the Matanuska Experiment Farm station noted a "distant earthquake," it is not unreasonable to assume that the earthquake was centered somewhere very near to Anchorage. There are several active faults near Anchorage – most notably the Castle Mountain Fault.

Whose fault was it?

Since very little information is readily obtainable about the earthquake, plus the fact that several thousand people were living in the area, it is reasonable to assume that it was not a magnitude 8+ event associated with the Aleutians Megathrust Fault. However, less intense, deep earthquakes associated with this fault can occur almost anywhere in southern Alaska.

A USGS report from 1999 suggests that magnitude 7.0 is the approximate upper limit of locally generated earthquakes in the Anchorage area. These faults are located close to the surface and would generate considerable shaking. Earthquakes close to the surface generally have more aftershocks. No mention of aftershocks are noted on any of the forms in regard to the 1922 earthquake  Since the Castle Mountain fault, the main active fault near Anchorage, has been studies extensively and no record of a 1922 quake exists along that fault line, it appears doubtful that this is the source of the earthquake. Figure 6 shows the locations of major fault lines in southern Alaska,


Figure 6. Major faults in southern Alaska. Modified from original image found at:  http://www.sciencemag.org/content/300/5622/1113/F1.large.jpg .


Given the aforementioned constraints, the descriptor "violent" in Anchorage, the newspaper account of the "Severe" effects in Seward, and the fact that it was felt in cities 400 miles apart, a strong argument can be made that this was a deep earthquake somewhere in the magnitude 7 range centered near Anchorage.

Some readers are far more knowledgeable about earthquakes than I am. Any assistance you can provide in finding more information about this event would be appreciated.

October 5, 2015 Postscript

I communicated with a researcher with several published articles on historic earthquakes in southern Alaska. They read the blog post and said it was entirely possible the earthquake magnitude might be as high as 7 on the Richter Scale. That assessment is based solely on the information presented in this blog post and is not a formal opinion.

Wednesday, February 4, 2015

Upper Level Pattern Length

Last year I began looking at how to quantify the length of temperature patterns at the surface. It seems like when the temperature goes above normal, it stays that way for a while. Conversely, cold patterns tend to hang around a while too. Unfortunately, what happens at the surface does not alway reflect what is going on synoptically. Just this week, Anchorage has stayed quite cold even though an above normal airmass moved overhead. At the surface, the airmass change went nearly unnoticed. Therefore, I decided to use 850 mb temperature changes as a proxy measure of airmass changes. There are certainly other metrics as well. We could looks at 500 mb or 300 mb winds or height changes. For now, those will be left for another day.

There has been discussion in the scientific literature over the last few years about changes in jet stream "blockiness." A blocky pattern should be reflected in longer duration of upper air patterns. Once again, because the data is handy for me, I will look at the Anchorage International Airport balloon soundings (1948-2014). As we noted last week, the temperature at 850 mb in Anchorage has been steadily rising. Therefore, we need to compute daily normal temperatures and standard deviations based on 30-year climate periods. Figure 1 shows the normal 850 mb temperature for Anchorage.


Figure 1. Normal temperature at 850 mb for Anchorage International Airport. Four 30-year periods are shown.

How do we decide if an above normal or below normal pattern is present? For this study, I arbitrarily decided that if 6 out of 7 days are in the upper tercile of temperatures (>= 0.43 standard deviations above the mean), all 7 of those days are part of a "warm spell." Conversely, if 6 out of 7 days are in the bottom tercile of temperatures (<= -0.43 standard deviations below the mean), all 7 of those days are part of a "cold spell." This is a "gut feeling" definition but will suffice for now. Figure 2 shows a sample of my Excel calculation output. Note the columns titled "Above" and "Below." They denote warm spells and cold spells in December 2013. In that month, there was a 9-day warm spell and an 8-day cold spell based on the aforementioned criteria.


Figure 2. Excel screenshot showing calculation of warm and cold spells.

Now for the fun part. Has there been a change in the length of these patterns since 1948? The answer is yes and no. Let's look at a chart first. Figure 3 shows the length of all warm and cold spells since 1948. Since the minimum length of a warm or cold spell is 7 days, that is the minimum value on the y-axis. It is difficult to discern patterns from all the dots; therefore, I added trend lines to the data.


Figure 3. Length of time for all warm ad cold spells at 850 mb in Anchorage. Each dot represents the end point of a period.

At the beginning of the balloon record, warm spells and cold spells each lasted 12 days on average. Over the next 67 years, the length of cold spells dropped slightly to 11.5 days and the length of warm spells increased by 25% to an average length of 15 days. This is a quite dramatic increase in my opinion. If we look at it on a decade basis, we see that the patterns are quite consistent on that time scale. Figure 4 shows the average length of warm and cold spells by decade.


Figure 4. Length of time for all warm ad cold spells at 850 mb in Anchorage grouped by decade.

Not only are temperatures rising at the 850 mb level in Anchorage, but the average length of a warm period is increasing. What is most interesting is that the increase in the length of warm spells is not coming at the expense of the cold spells.

Tuesday, February 3, 2015

U.S. Winter Weather Advisories and Warnings

How wintry is it where you live? Well, that is a tough question to answer. As with many measures of comfort, it really is in the eye of the beholder. Ever since I discovered the NWS forecast product archive, I have wanted to look at NWS forecasts as a proxy measure of wintry-ness.

Introduction

In 2005, the National Weather Service (NWS) made a significant change to the way they issue watches and warnings. They introduced the VTEC coding system to standardize the procedure for issuing these products. The VTEC code allows various software packages to quickly decode the forecast product and display it on a map or transmit the information to subscribers and the public. Figure 1 shows a sample forecast product with the VTEC code outlined in red. The VTEC line notes that it is operational, a new issuance, from the Fairbanks NWS Office, a winter weather advisory, and the start/end times are noted.

Figure 1. Winter Weather Advisory issued by the Fairbanks, Alaska, NWS office on January 1, 2015. The VTEC is outlined in red.

The University of Iowa generously logs all NWS forecast products from every office in the country. Their archive site is quite handy for analysis of historical data. Unlike many data archive sites, they are perfectly happy to let you grab data using your own scripts and other tools. They even provide some sample Python scripts for you to use. Thank you Daryl Herzmann!

Winter Weather Products

In this analysis, I am interested only in winter weather products issued by various NWS Offices. Each NWS Office is responsible for all forecasts within their zones (except for severe thunderstorm and tornado watches). Figure 2 shows the NWS Offices in the U.S. and Figure 3 shows the forecast zones for the U.S. For most of the U.S., forecast zones share boundaries with counties. However, this is not always the case.

Figure 2. Map of all NWS Offices in the U.S.

Figure 3. Map of all NWS forecast zones in the U.S.

Local Criteria

With the exception of Blizzard Warnings, the criteria for every winter weather product is defined by the local NWS office. For example, the Wind Chill Advisory criteria for most of Alaska requires wind chill value of -40° or lower with a sustained wind of 15 mph or higher for three or more consecutive hours. In southern Florida, a wind chill of +35°F is sufficient for issuance of a Wind Chill Advisory. Therefore, southern Florida has seen more Wind Chill Advisories than most of Alaska! Unfortunately there is not a single repository for local advisory criteria. The NWS Central Region and NWS Alaska Region have winter criteria summaries but the other regional offices no not. Therefore, a comparison of the number of advisory and warning products is an apples to oranges comparison – but it is fascinating nonetheless. 

Maps

In this section we present eleven (11) maps of winter weather advisory products. For all maps, we use the 2009-2014 time period. The reason for this is because significant changes were made to the suite of forecast products in 2008. For example, Snow advisories and Freezing Drizzle Advisories were consolidated into Winter Weather Advisories. Due to these changes, I thought it best to start in 2009 instead of parse out the pre-2009 data. Please keep in mind that these are forecast products. No attempt has been made to assess the accuracy of the forecasts.

And here are the maps .....

Figure 3. Combined number of Frost Advisories, Freeze Warnings, and Hard Freeze Warnings between 2009 and 2014.

Figure 4. Number of Freezing Fog Advisories between 2009 and 2014.

Figure 5. Number of Freezing Rain Advisories between 2009 and 2014.

 Figure 6. Number of Ice Storm Warnings between 2009 and 2014.


Figure 7. Combined number of Wind Chill Advisories, Wind Chill Warnings, and Excessive Cold Warnings between 2009 and 2014.

 Figure 8. Number of Winter Weather Advisories between 2009 and 2014.

Figure 9. Combined number of Lake Effect Snow Advisories and Lake Effect Snow Warnings between 2009 and 2014.

Figure 10. Number of Winter Storm Warnings between 2009 and 2014.

Figure 11. Number of Blizzard Warnings between 2009 and 2014.

Figure 12. Total number of winter precipitation-related advisories (Winter Weather, Lake Effect Snow, and Freezing Rain) between 2009 and 2014.

Figure 13. Total number of winter precipitation-related warnings (Winter Storm, Lake Effect Snow, Ice Storm, And Blizzard) between 2009 and 2014.

There are far too many patterns in the maps to mention. The patterns are a result of climatology, forecast criteria, and forecaster judgement. Is there anything that surprises you?

Note: While I attempted to accurately portray the data depicted above, I cannot guarantee it is error-free.