(1) Only using data from one or two stations that could, at times, produce 'false surge' results due to their proximity to the GoC
(2) Not using precipitation as a classification variable
To avoid (1) we are using a spatially and temporally continuous dataset over a broad region that is tied to the NAM system. But, as of yet, I have not done much about (2). In my opinion, using dewpoint as a criteria for a surge event and not precipitation seems to be missing the point of finding this events, i.e., forecasting precipitation for the arid southwestern US. To this end I have decided to try some new avenues for classifying these events. Below I will show what work I have done in regards to DWP, IWVF and PRCP as variables and new thresholds.
To get an understanding of how dynamic an indicator each of my proposed variables truly is, I calculated the coefficient of variation for each. The coefficient of variation is a measure of dispersion of a variable and is dependent on the standard deviation divided by the mean. The usefulness of this measure is that it provides a means to compare different variables with different units. The coefficient of variation for DWP, IWVF and PRCP were 0.0166, 0.7232, and 1.5035, respectively. Values of 1 or greater are an indicator of a highly dispersed variables. Therefore, PRCP is our most dynamic indicator. Though not exceeding 1, IWVF does show signs of being changeable. Notably, DWP shows very little to no variability. Fig 1 is a composite of the DWP anomaly field in association with days where PRCP meets or exceeds 1-sigma over its mean (more on this criteria later). The darkest blue (red) is related to an anomaly of 0 (4) degrees Celsius above the mean. DWP shows some activity, but, interestingly, this activity is mainly located in extreme southern Nevada and not the core region normally associated with NAM activity in the US. I want to point out that where most previous studies have relied on data from, i.e., Yuma, actually shows little to no change during these events.
Fig 1: DWP Anomalies where dark blue (red) corresponds to 0 (4) degrees Celsius anomalies.
So, from this, I have come up with the following criteria for classification:
Event = IWVF meets or exceeds 1-sigma over mean on the same day that PRCP meets or exceeds 1-sigma over mean.
Some of this stems from conversations with Dr. Cordero about statistics (or what the BeeGee's might call "Stat Talkin' ") and how to find physically meaningful characteristics through statistical analysis. Initially, I was looking for events of 2-sigma above mean, but this did not provide results that I felt were very realistic, i.e., very few events. DWP never actually exceeds 2-sigma in our study period. Here our some of the numbers to go along with this criteria:
# of Events (1980 - 2007) = 172
~ 6.14 per year
~ 1.54 per month
I believe, and also through talks with Mike, that 1.5 events per month is a more realistic climatological number of surge events, not 3.
Here are some of the intra-seasonality of the numbers:
June: 3
July: 53
August: 64
September: 52
Fig 2 is a composite of IWVF anomalies, mean fields of Meridional IWVF, and PRCP anomalies associated with these events.
Fig 2: Composites for IWVF anomaly (top), mean Meridional IWVF (middle) and PRCP anomaly (bottom) fields in relation to events. For Meridional IWVF dark blue (red) corresponds to 0 (20), and for PRCP anomalies dark blue (red) corresponds to 0 (6) mm per day anomalies.
Fig 3 are the results for July of 1986 compared to those of Fuller and Stensrud (2000), their Fig 2. Their events are highlighted in blue (W = weak and S = strong events) and mine are in red. Units for IWVF (red, dashed line) and PRCP (blue, solid line) are on the left (green, dotted line) and DWP is on the right.
I was not able to put this image on the site because I updated it with PPT. Here is a link: http://www.met.sjsu.edu/~favors/Research/July1986_IWVFPRCPDWP.ppt
