Tuesday, April 21, 2015

Alaska Size Comparison Maps

The fun little map I made the other day while my kids were watching a movie showing the size of Alaska compared to other states really took off. In response, I put together this new set of maps where different states are used. Some states are used in more than one map and others appear only once. The states are depicted in an Albers equal area map projection. As the name implies, an equal area projection leaves the relative sizes of the states proportionally accurate. Feel free to share these maps with your friends, but please talk with me first before placing them on printed materials.

And now, the maps ....











Friday, April 17, 2015

Alaska High Temperature Categories

** Note: this is the Alaska-centered version of this blog post. For the Contiguous U.S.-centered version, click HERE. **



"Today's high temperature will be in the 60°s." - unknown

Official, unofficial, anecdotal, and other communication mediums frequently discuss temperature forecasts in terms of 10-degree Fahrenheit temperature ranges. While greater precision in forecasts is always available, using these broad temperature categories is fairly useful.

Looking at longer time-scales, these types of temperature categories are especially useful. Me might say, for example, that Dallas, Texas, is typically in the 90°s during the month of June. This gives a meaningful description of the early-summer climate at that location without confusing it with an actual forecast. If we expand upon the brief example for Dallas, Texas, it might be useful to ask ourselves how common are days in the 90°s at Dallas and at other places across he U.S. Why stop with 90°s? What about 80°s, or 50°s, or 20°s?.

Methodology

To find the answer to this question, we need to look at high temperature data for as many stations across the U.S. as possible. The National Climate Data Center (NCDC) maintains an archive of daily climate data for thousands of stations across the U.S. as part of the Global Historical Climatology Network (GHCN) database.

For this analysis, I placed three restrictions on the data. 1) only data since 1981 were utilized, 2) stations must have 10+ complete years of data, and 3) only WBAN (first-order) stations were used.

The first criteria allows us to closely mirror the current 1981-2010 climate normal period employed by the NCDC. The second criteria just makes sure enough data to draw meaningful conclusions. The third criteria has to do with the processing power and memory limitations of my computer.

Using the aforementioned selection criteria, a total of 985 stations contained sufficient data for inclusion. A map of those stations is shown in Figure 1.

Figure 1. All WBAN stations with at least 10 years of complete high-temperature data since 1981.

10-Degree Category Maps

The following section contains 12 maps each representing the number of days per year with a high temperature in a 10°F range. For example, how many days have a high temperature in the 90°s? This query would include all days with a high temperature greater than or equal to 90°F and less than or equal to 99°F. The first and last maps represent categories greater than 10°F; e.g., days with a high temperature less than 0°F, and days with a high temperature greater than or equal to 100°F. Please note that no attempt was made to account for elevation in mountainous areas.

Figure 2. Number of days per year with a high temperature below 0°F.

Figure 3. Number of days per year with a high temperature in the +0°s (0°F to 9°F).

Figure 4. Number of days per year with a high temperature in the 10°s (10°F to 19°F).

Figure 5. Number of days per year with a high temperature in the 20°s (20°F to 29°F).

 Figure 6. Number of days per year with a high temperature in the 30°s (30°F to 39°F).

 Figure 7. Number of days per year with a high temperature in the 40°s (40°F to 49°F).

 Figure 8. Number of days per year with a high temperature in the 50°s (50°F to 59°F).

 Figure 9. Number of days per year with a high temperature in the 60°s (60°F to 69°F).

 Figure 10. Number of days per year with a high temperature in the 70°s (70°F to 79°F).

 Figure 11. Number of days per year with a high temperature in the 80°s (80°F to 89°F).

 Figure 12. Number of days per year with a high temperature in the 90°s (90°F to 99°F).

Figure 13. Number of days per year with a high temperature 100°F or above.

Figure 14. Most common 10° high temperature group.

Wednesday, April 15, 2015

U.S. High Temperature Categories

** Note: this is the Contiguous U.S.-centered version of this blog post. For the Alaska-centered version, click HERE. **



"Today's high temperature will be in the 60°s." - unknown

Official, unofficial, anecdotal, and other communication mediums frequently discuss temperature forecasts in terms of 10-degree Fahrenheit temperature ranges. While greater precision in forecasts is always available, using these broad temperature categories is fairly useful.

Looking at longer time-scales, these types of temperature categories are especially useful. Me might say, for example, that Dallas, Texas, is typically in the 90°s during the month of June. This gives a meaningful description of the early-summer climate at that location without confusing it with an actual forecast. If we expand upon the brief example for Dallas, Texas, it might be useful to ask ourselves how common are days in the 90°s at Dallas and at other places across he U.S. Why stop with 90°s? What about 80°s, or 50°s, or 20°s?.

Methodology

To find the answer to this question, we need to look at high temperature data for as many stations across the U.S. as possible. The National Climate Data Center (NCDC) maintains an archive of daily climate data for thousands of stations across the U.S. as part of the Global Historical Climatology Network (GHCN) database.

For this analysis, I placed three restrictions on the data. 1) only data since 1981 were utilized, 2) stations must have 10+ complete years of data, and 3) only WBAN (first-order) stations were used.

The first criteria allows us to closely mirror the current 1981-2010 climate normal period employed by the NCDC. The second criteria just makes sure enough data to draw meaningful conclusions. The third criteria has to do with the processing power and memory limitations of my computer.

Using the aforementioned selection criteria, a total of 985 stations contained sufficient data for inclusion. A map of those stations is shown in Figure 1.

Figure 1. All WBAN stations with at least 10 years of complete high-temperature data since 1981.

10-Degree Category Maps

The following section contains 12 maps each representing the number of days per year with a high temperature in a 10°F range. For example, how many days have a high temperature in the 90°s? This query would include all days with a high temperature greater than or equal to 90°F and less than or equal to 99°F. The first and last maps represent categories greater than 10°F; e.g., days with a high temperature less than 0°F, and days with a high temperature greater than or equal to 100°F. Please note that no attempt was made to account for elevation in mountainous areas.

Figure 2. Number of days per year with a high temperature below 0°F.

Figure 3. Number of days per year with a high temperature in the +0°s (0°F to 9°F).

Figure 4. Number of days per year with a high temperature in the 10°s (10°F to 19°F).

Figure 5. Number of days per year with a high temperature in the 20°s (20°F to 29°F).

 Figure 6. Number of days per year with a high temperature in the 30°s (30°F to 39°F).

 Figure 7. Number of days per year with a high temperature in the 40°s (40°F to 49°F).

 Figure 8. Number of days per year with a high temperature in the 50°s (50°F to 59°F).

 Figure 9. Number of days per year with a high temperature in the 60°s (60°F to 69°F).

 Figure 10. Number of days per year with a high temperature in the 70°s (70°F to 79°F).

 Figure 11. Number of days per year with a high temperature in the 80°s (80°F to 89°F).

 Figure 12. Number of days per year with a high temperature in the 90°s (90°F to 99°F).

Figure 13. Number of days per year with a high temperature 100°F or above.

Figure 14. Most common 10° high temperature group.


Monday, April 13, 2015

Severe Weather Time of Day



When are severe thunderstorms most likely to occur? This is a question of great interest to forecasters, researchers, and emergency management personnel.

A number of sites contain bar charts or broadly generic maps with severe weather frequency (see here and here). However, a detailed temporal climatology does not appear to exist. Therefore, I present these maps as a jumping off point for continued discussions.

The Storm Prediction Center (SPC) has an wonderful archive of past severe thunderstorm climatology. Their database was used exclusively in the development of these severe weather climatology maps.

Severe Weather Definitions

Before we get started, here is what defines "severe weather" and therefore included in the SPC database.

1) Wind gust in excess of 50 knots (associated with a thunderstorm)
2) Hail 1" or greater in diameter (>25 mm)
3) Tornado

The SPC database contains hundreds of thousands of events as a series of points and lines. Each record in the database is assigned a latitude, longitude, and time of occurrence. Since an event with a beginning and ending coordinate (a line) is only assigned a single time stamp, I decided to assign the time to the beginning coordinate and treat the event as a discrete point.

Unit of Time

Every chart that I have come across relating severe weather to a time of day uses clock frequency. In the example from the NWS Wichita office, they determined that the 5:00 p.m. - 5:59 p.m. hour is the most likely hour to observed a tornado in their region. While this is useful information, it is not applicable to all places. Imagine two cities with an identical tornado climatology, but at opposite sides of a time zone. They have a chart that is an hour different – even though the peak may be exactly the same. Next, the time of peak solar energy is not the same from day-to-day. It changes by nearly 30 minutes over the course of a year. The Equation of Time describes the changes in the time of solar energy. Since the primary source of energy that drives severe thunderstorms is diurnal solar input, knowing the exact solar parameters for an event is crucially important.

A simple relationship exists between the longitude and the time of solar noon (when the sun is at its maximum elevation above the horizon). This value is easily computed from the date and the longitude entries in the severe weather databases. A correction based on the Equation of Time is then applied the the solar noon calculation. Finally, the solar noon time is subtracted from the event time to come up with our units. For example, if a city's unadjusted solar noon is 12:30 p.m., the Equation of Time correction for that date is -0:15, and a severe hail storm hit at 4:45 p.m., the event is computed as occurring 4.5 hours after solar noon. Therefore, severe weather times of occurrences are described as hours after solar noon.

Data Processing

Since solar energy is the main, but not exclusive, driver of severe weather, I took the liberty of removing some events. Specifically, all events in the months of December, January, and February were excluded. Also, events that occurred between 3.5 and 8.5 hours before the computed solar noon were removed. Here's why. If an event happened at 6 a.m. on a day where solar noon was computed as 12:00 p.m., did the event happen 6 hours before solar noon or 18 hours after yesterday's solar noon? This is a difficult question to answer. So, I just removed 5 hours worth of observations and made the problem go away.

For each data set (tornado, hail, and wind) I made a density grid for the entire U.S. using 35,000 meter grid cells. if a grid cell had at least 4 events during the period of record, it was kept for analysis. This leaves out most of the area west of the Rocky Mountains.

Next, an average value of the time past solar noon for all events in each grid cell was computed. In it's raw form, this makes the map look quite chaotic. To make it aesthetically pleasing, I ran a 5x5 mean filter across the data sets.

Maps

The following three maps were generated using the process described in the preceding section.

Figure 1. Average time of occurrence of all severe thunderstorm-generated wind events. Time is hours after solar noon.
Figure 2. Average time of occurrence of all large hail events. Time is hours after solar noon.

Figure 3. Average time of occurrence of all tornado events. The time is assumed to represent the point of initial tornado touchdown. Time is hours after solar noon.

Figure 4. Average time of occurrence of all severe weather events. Time is hours after solar noon.


Analysis

I was quite surprised at the time variability in Figures 1 & 2 in particular. Why are storms more likely to occur several hours later in the day in the Great Plains versus the eastern 1/3 of the U.S.? Could it be the continentality of the Great Plains airmass takes several additional hours to heat up after a cool night? What about Florida? Why is their severe weather so much earlier in the day? I don't really have the answers to the questions. What do you think?