Why is doppler radar used in weather prediction

Computers analyze the strength of the returned pulse, time it took to travel to the object and back, and phase, or doppler shift of the pulse.

This process of emitting a signal, listening for any returned signal, then emitting the next signal, takes place very fast, up to around times each second! When the time of all the pulses each hour are totaled the time the radar is actually transmitting , the radar is "on" for about 7 seconds each hour.

The remaining 59 minutes and 53 seconds are spent listening for any returned signals. Learn about the different scanning modes of the Radar here. The phase of the returning signal typically changes based upon the motion of the raindrops or bugs, dust, etc.

This Doppler effect was named after the Austrian physicist, Christian Doppler, who discovered it. You have most likely experienced the "Doppler effect" around trains. As a train passes your location, you may have noticed the pitch in the train's whistle changing from high to low. As the train approaches, the sound waves that make up the whistle are compressed making the pitch higher than if the train was stationary. Likewise, as the train moves away from you, the sound waves are stretched, lowering the pitch of the whistle.

The faster the train moves, the greater the change in the whistle's pitch as it passes your location. The same effect takes place in the atmosphere as a pulse of energy from NEXRAD strikes an object and is reflected back toward the radar. The radar's computers measure the phase change of the reflected pulse of energy which then convert that change to a velocity of the object, either toward or from the radar.

Information on the movement of objects either toward or away from the radar can be used to estimate the speed of the wind. This ability to "see" the wind is what enables the National Weather Service to detect the formation of tornados which, in turn, allows us to issue tornado warnings with more advanced notice.

In the image above, the grey line is the transmitted signal. You can see how the returned energy changes its wavelength characteristics when it hits a target moving away or toward the radar red and green line, respectively. There are two main types of data, Velocity and Reflectivity.

Reflectivity data shows us the strength of the energy that is returned to the radar after it bounces off precipitation targets. Other non-precipitation targets will return energy, but for now, we will only deal with the precipitation. In general, the stronger the returned energy, the heavier the precipitation. Learn more about Reflectivity here. Velocity data is derived from the phase, or doppler shift of the returned energy. The radar's computers will calculate the shift and determine whether the precipitation is moving toward or away from the radar, and how fast, then apply a corresponding color to those directions and speeds.

Latest Newscasts. Investigate TV. Gray DC Bureau. Breakdown: Why doppler radar is an important tool. By Nick Gunter. Updated: Feb. Share on Facebook. Email This Link. Share on Twitter. Share on Pinterest. Share on LinkedIn. Consequently, some of the committee's recommendations deal with such procedural issues. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

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Get This Book. Visit NAP. Looking for other ways to read this? No thanks. Suggested Citation: "1. Page 9 Share Cite. Such knowledge has greatly benefited the operational utility of weather radar, particularly through innovations, understanding, and testing of algorithms that process radar data into meaningful physical descriptions of atmospheric phenomena and weather con- 1 A complete list of acronyms and their definitions is provided in Appendix B.

Page 10 Share Cite. Page 11 Share Cite. Recommendation 2 The next generation of radars should be designed as part of an integrated observing system aimed at improving forecasts and warnings on relevant time and space scales. Page 8 Share Cite. The component of velocity orthogonal to the radial line is undetectable by radar. This is the zero isodop problem. But I'm not hands on and will defer to a better knowledge. I mean, unless the radar is pointing directly up or down?

The targets in this case, raindrops falling from clouds, is typically removed from the radar site by tens of kilometers. This means the vertical component of the falling rain is more or less undetectable, as is the horizontal component of velocity that is orthogonal to the line from the radar site to the clouds. Combining results from multiple doppler radar give a nice 2D view of the rain, but the vertical component remains more or less undetectable.

But I also see your point that the radial component of far-away vertical movement is very small. Doppler detects wind velocity more specifically, range rate. Older radar systems did not. This added dimension significantly improved short term forecasts of severe weather. The OP asked how it is used to predict rain, not for an engineering explanation of how it functions of trivia like how until software AI was improved it could not tell the difference between a swarm of insects and a storm.

I know about the vector differentials and side slip analysis which is analysed to signal potential wind sear and vortex formation, none of which is important to his question but is very important as to why millions of dollars were spent to upgrade to newer technology.

Those are compared to past similar conditions and a determination of the likelihood of a repeat is calculated and relayed. It is a vast improvement over look out a window and saying "Looks like rain". Sign up or log in Sign up using Google.

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