|George R. Kasica
METEO 241 Portfolio #3: Reflections on lessons learned from hurricane Rita
Looking back on hurricane Rita and I decided to examine it's life cycle at a number of points and also look at a number of variables that allowed to to organize and strengthen into a category five storm, the most intense on the Saffir-Simpson rating scale.
To begin with I examined it's formation as an easterly wave off the west coast of Africa. By doing this I gained a very good understanding of how many hurricanes form and what their ultimate origins are. Prior to this portfolio I had assumed that most hurricanes formed and grew in intensity in the areas not far from the SE US coast and the Caribbean Island areas. Learning that the storms actually formed thousands of miles farther to the east was something that was surprising to me and new knowledge that I will use going forward to observe and look at storms such as these in the future. In particular it will prompt me to look for meteorological conditions far more distant and much earlier than I had in the past in observing hurricanes.
The next phase of examining hurricane Rita was to look at the storm's track and why it followed the path that it did. In analyzing this aspect of the storm I learned that the storms are actually steered by a much broader and deeper wind flow than I has suspected in the past. Prior to taking this course I had assumed that the storms had a much more independent and random nature to their track and ultimate destination. By looking at hurricane Rita I learned that they are in fact steered and influenced in their track much the same way as other weather systems. This realization also helped me to understand why it is possible to predict with some accuracy where they storms will ultimately move and when, as the same principles and mathematical models can be used as a basis for forecasting their movements as are used for more conventional mid-latitude systems that we are more familiar with.
A third area that I studied was the combination of three critical ingredients that allowed the storm to rapidly intensify from a somewhat poorly organized tropical storm with winds about 60 kts. to a massive category five hurricane with winds near and exceeding 145kts. in just about 36 hours time. In looking at the three items that allowed this to happen (sea surface temperature, mid-level relative humidity and vertical wind shear) I learned that it is not as simple or easy as it appears to have a strong hurricane such as Rita became in September 2005. In reality if any of the the above items were not present at the proper time or in the correct quantities chances were very good that the storm would not have become as strong as it did. In the past I didn't realize how delicate that combination of ingredients was or how even a minor change in the timing or quantities of them could affect the ultimate strength of the storm, I had assumed that the storms strengthened and weakened in a much more random fashion. Again, given that the effects of these and other variables can be measured and predicted I learned how its is possible to predict with some accuracy the strength of the storm at a given time.
The last area I looked at was a visually interesting effect known as the stadium effect. The cause of the effect is more technical and difficult for me to understand and explain than other areas of the storm, but the visual evidence of it's existence is quite obvious and striking in the high resolution images that I included in the section. In this area I learned that even with very powerful storms and incredible potential for destruction, you can find very visually beautiful items to look at. The fact that we are able to obtain these types of images at that level of resolution was a learning point for me. I was aware of more normal satellite images that we are used to seeing on TV everyday when we watch a weather forecast or search out on the Internet to make our own forecasts. By looking at the storm in this manner I was able to realize that we are able to take images with resolutions of items down to as small as 250 meters in size from several hundred miles in space is something I wasn't aware was available to anyone that wanted to see that detail by simply looking at a site on the Internet.
Now that I've completed the course on Tropical meteorology I can see several ways in which I have gained new knowledge and increased my understanding of tropical weather systems. As I mentioned in the beginning of the course in the first e-portfolio's reflection area,
As a result of these interests I tended to concentrate my studies here on the different techniques of remote observation and how the storms could be predicted and forecast using computer forecast models. In the course I learned about several new types of satellite observation techniques such as scatterometry (the remote measurement of wind speeds by satellite), the high resolution visual images I mentioned above that allowed me to observe the stadium effect, and also the ability to measure rainfall by satellite via the TRMM satellites. In terms of computerized forecasting concepts and techniques I learned that the storms in fact follow rules and principles similar to what I was used to seeing for more conventional weather systems over the US. As a result I learned that the numerical models are able to predict the path and intensity of the storms with some accuracy rather than a much more random nature as I had assumed before.
Another realization that I came to was that many things in the tropical weather environment are not well understood or as easy to quantify as say a typical storm system in the continental US would be. I came to this realization while I was looking at the effects of El Nino,
This concept was far more difficult for me to grasp and put to use than the more concrete and quantitative items that I mention above relating to remote sensing, numerical prediction and high resolution images. I think the reason that this area gave me so much difficulty was that the effects of El Nino are far more wide reaching, yet far less easily traced back to the phenomena than say the damage from a category five hurricane. We learned that you cannot necessarily blame any one discrete event on the more global effect of El Nino, yet it most definitely can be shown that El Nino has a substantial impact on the large scale weather patterns of the western US for example as I looked at in my second e-portfolio.
Overall as a result of this course I discovered that tropical meteorology is both much more predictable in some sense (such as the strength and track of a hurricane) and yet much less easy to quantify and connect to discrete day to day weather events (in the case of El Nino). In the future I would like to continue to examine the different ways available for forecasters to remotely sense hurricanes and have begun to do additional reading in this area. I also an interested in how they can use numerical prediction to track the path and intensity of the storms, and as a result of this I have started working with a Windows-PC based version of a forecasting model WRF) that I hope to be able to put not only past data into it but eventually make near real-time forecasts into the future. Whether this can be applied to hurricanes as well as more traditional forecasting is something I hope to discover and it will allow me to further combine my interests in both computer technology and weather forecasting.