Well, after getting 100,000+ classifications, we thought it was time to let you – the citizen scientists – know that you’re doing a great job!
Q: What did you find?
A: During our preliminary analysis, we have observed some results that encouraged us – the science team – so we thought it would encourage you – the citizen scientists.
Q: What did you analyze?
A: So far, we have not looked at detailed classifications (which should give the best estimate of intensity) but just the initial scene type classification. That is, we looked at how each scientist answered “Pick the cyclone type, then choose the closest match.”
Q: How did you analyze that data?
A: We assigned a number based on the scene selected – what I’ll call an Image Scene Number, or ISN. We then averaged the ISN for each image of a storm and did some analysis to get what we think is a current best estimate of an ISN. The results were surprisingly good based solely on this Image Scene Number. Further statistical analysis is needed (these initial results were obtained using simpler methods).
Q: What do we learn from the initial analysis?
A: Well, remember the analysis is still very preliminary. This is a real result for one cyclone in our 3000+ record of cyclones. What we want others to know is:
- Citizen scientists are doing a great job, but much more needs to be done. Every click counts!
- The science team is working with the data and are encouraged that some more initial results could be shown soon (within a year).
- The initial results show a similar pattern as the best track data. We are in the right ballpark! Further refinement and better statistical methods should refine the results.
Q: Can we see the results?
A: Yes! Now remember, these are still very preliminary, but here is the analysis so far for 1990 Hurricane Trudy.
- The time axis has the same reference start date.
- The boxes are the average ISN.
- The vertical lines represent the variation in ISN between multiple classifications. The larger the bar, the less certain we are of that value.
- The numbers along the bottom are the number of classifications averaged.
- When only one classification was available, the variation is zero (square with a dot in it). The dot does not mean no variation, but only that we don’t have enough classifications to estimate the variation.
- The ISN pattern captures the peaks in intensity near day 4 and 11 !
- So far, there seem to be more classifications in the early portion of the storm’s lifetime than later (lots of images with only 1 classification after day 7). This will change as more classifications are made.
- The valley (the weaker intensity around day 7) appears in both the best track and the initial analysis.
Q: Why 1990 Trudy?
A: Well, the results here were good and it shows an interesting intensity where it peaks as a strong hurricane, then weakens, then increases again before finally ending. Some other cyclones showed similar results. Much more analysis is needed before we can say how well the scientists and the analysis website are performing. But regardless, these results are promising!
Q: Why use ISN (Image Scene Number)? Why not something from the Dvorak method?
A: The technique used here is based on the Dvorak Technique for analyzing tropical cyclone intensity. In that method, there is a measure of intensity call the Pattern T-Number (called PT). While our method is based on Dvorak, it is not an exact representation of the Dvorak values. So ISN (Image Scene Number) is analogous to the Pattern T-number, but is not an exact match. Rather than confuse the two methods, we will try to define our values clearly and, where possible, will state if there are analogous parameters in the Dvorak method.