To make the maps shown in the figures below, we used the NCDC 1981-2010 normal monthly precipitation values for 8,535 stations in the 50 states. For each station, the month with the greatest normal precipitation was identified. There were 98 stations that had a tie for the wettest month and 1 station with a three-way tie for the wettest month. In the monthly maps that begin with Figure 4, stations that were tied are shown in any month where the tie exists.
Nationwide Wettest Months and Seasons:
Before we begin with the map set, please take the opportunity to download a Google Earth file with all 8,535 stations that are color coded by the wettest month. Each station's monthly precipitation data can be viewed by clicking on the station's marker.
The first 3 figures show the wettest climatological season (Figure 1) and the monthly peak precipitation values (Figures 2, 3).
If we define the seasons by traditional climatological boundaries (Dec-Feb, Mar-May, Jun-Aug, and Sep-Nov) and add up the normal precipitation values for each of those time periods, we can easily identify which season is the wettest. Figure 1 shows the result of that analysis. Since there are only four categories, the seasonal boundaries are quite easy to discern. The West Coast has a winter precipitation peak and most of the rest of the country sees a summer peak – with the notable exception of an area bounded by Central Texas to the Ohio River Valley to the Deep South.
Unlike the seasonal map, the combined monthly maps are much more difficult to visualize. That being said, it is important to distinguish between a January peak and a December peak (for example). Figures 2 and 3 show the station breakdown by calendar month – one as a dot map and the other as a color scale (choropleth) map. For example, the Spring maximum noted in Figure 1 is shown in Figure 2 to be nearly entirely composed of stations whose wettest month is May. To the west of the May stations, a large area of June stations exist. While the seasonal map showed a significant break in the region, it is relatively minor when looking at the monthly data. However, a sharp transition to Winter peak values exists to the east of the May stations. Again, having the monthly values is important for this type of assessment.
Figure 3. Continuous map of wettest month of the year.
Instead of trying to decipher (often) complicated patterns, I though it useful to have an individual map for each month of the year. In the following 12 figures (Figures 4 through 15), each month of the year is pulled out individually. Only those stations with a peak precipitation value in that month are shown. If a station has a tie for the peak month, it is shown on all maps for which a tie exists.
Figure 4. Stations where the wettest month of the year is January (n=277).
Figure 5. Stations where the wettest month of the year is February (n=332).
Figure 6. Stations where the wettest month of the year is March (n=263).
Figure 7. Stations where the wettest month of the year is April (n=76).
Figure 8. Stations where the wettest month of the year is May (n=1,881).
Figure 9. Stations where the wettest month of the year is June (n=2,053).
Figure 10. Stations where the wettest month of the year is July (n=1,073).
Figure 11. Stations where the wettest month of the year is August (n=916).
Figure 12. Stations where the wettest month of the year is September (n=438).
Figure 13. Stations where the wettest month of the year is October (n=339).
Figure 14. Stations where the wettest month of the year is November (n=333).
Figure 15. Stations where the wettest month of the year is December (n=653).
In many cases there are substantial difference between wet and dry months. Some stations in California and Alaska receive 60% of their annual precipitation in a three-month window. On the flip-side, many stations in the Northeast and mid-Atlantic have precipitation evenly distributed across all months.
The final map in this blog post (Figure 16) shows the month-to-month variability in precipitation values across the year. To make this map we calculated the difference between the NCDC normal precipitation for each month and compared it to the value that would occur if each month received 1/12th of the annual precipitation. This type of assessment is called a goodness-of-fit test. In this case we used the Chi Square goodness-of-fit-test.
As you can see, some areas have low month-to-month variability and others have quite a bit. I had assumed that all cold regions would have low winter precipitation values due to the moisture capacity of the air being greatly reduced. However, that is only the case in the Northern Great Plains and Alaska – not in New England. The other quite surprising finding is the low month-to-month variability in the Great Basin. Perhaps this is an artifact of multiple synoptic-scale parameters in other regions that all converge in this region.
There are far too many patterns in this map to describe. It is worthy of its own blog post another day!