My first industrial job after graduating with a PhD in theoretical physics was that of an R&D engineer at RCA, which at the time was a major conglomerate in the US. They manufactured TV sets among many other products which used cathode ray tubes (CRTs) as display devices. The charter of my group was developing magnetic deflection coils for CRTs which could deflect electron beams inside the tube to their desired positions. These coils had been traditionally designed by veteran engineers using their experience and intuitive skill following empirical trial and error methods a time consuming and expensive process. Our goal was to develop a CAD method using sophisticated computer programs so that design could be done faster and more accurately, even by less experienced engineers.

The staff members at the Research Laboratory, consisting mostly of PhDs in physics and mathematics, had already developed a program which they hoped would serve the purpose. Our job in the R&D group was to confirm its accuracy and give the research guys feedback so that they could continue to improve the software. The CRTs used in colour TVs used not one but three electron beams, one for each of the three “primary” colours, red, green and blue; colours were generated by phosphor stripes corresponding to each color, deposited on the inside of the TV screen. The desired performance was convergence of all three beams at every point on the TV screen.

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Our first task was to model an existing coil system to see how close its computer-predicted convergence characteristics came to its experimentally measured performance. While the computer model correctly predicted general trends such as geometric distortions, change in performance by incremental changes in design parameters, ideal location of the coils on the CRT, it never gave us a satisfactory number for “misconvergence error” – the separation between the red and blue beams, the most significant performance parameter. The largest error allowed in specifications was at the corners and typically of the order of 1-1.5 mm. Much to our frustration, the discrepancy between experimental value and computer prediction was 3 mm or more at corners, even after many enhancements of the software. As a result, neither RCA nor any other TV manufacturer succeeded in designing deflecting coils entirely using computer software.

The reasons for this discrepancy were understandable. In any physicsbased computer modeling there are two key components: a) construction of a “model” and b) actual mathematical computations. It is the second part that got more and more sophisticated with the introduction of faster computers and more innovative algorithms. Construction of a model is a different story. A model is absolutely necessary because we cannot convert everything we see into mathematical equations which the computer can crunch. A model inherently consists of a series of simplifying assumptions. For example, the earth can be modeled as a sphere but one must use a bunch of straight lines and triangles to model a tree. In modeling deflection coils, two major assumptions were: a) coils were assumed to be smooth two-dimensional surfaces which ignored discreetness and thicknesses of copper wires in the winding and b) electron beams were represented by rays without finite width. This resulted in uncertainties in computed values. This experience shaped my views about climate change predictions.

I am certainly not a climate change denier. As a physicist, I do believe endless carbon dioxide emission into the atmosphere is detrimental. Any effort to reduce such emissions is good. However, I draw the line at fanaticism in the name of science. I cringe when I hear predictions such as rise of ocean level by X ft by a certain year, flooding entire countries. Different models are used by scientists around the world and not surprisingly, their predictions do not all agree. Instead of electrons moving in a CRT we must now study the motion of earth dragging its atmosphere under the influence of the sun. Physics involved is much more complicated and often unknown; one must take into account an array of different interactions; the ones between sun, earth, moon, gas molecules, oceans, rotation of the orbs, exhaust from fossil fuel, deforestation and the list goes on. I am sure that these phenomena are taken into account in all models but my main point is that descriptions fed into software are oversimplifications of the real situation. Yes, the models will predict gradual warming, rising ocean levels and changes in many atmospheric phenomena, but they cannot possibly predict the timeframe and severity of their occurrence. This has nothing to do with denying science or questioning the mathematical rigour involved in the computation.

To make the predictions even trickier, we have no way of knowing the occurrence of natural phenomena like volcanic eruptions, earthquakes, underground lava flow and forest fires over upcoming decades and how different countries will attempt to reduce carbon dioxide emission or melting of ice caps. The weathermen on TV cannot even accurately predict weather for the next seven days! The real question is what we should collectively do at the present time. We must certainly do things that common scientific sense dictates: plant more trees, use solar energy, reduce use of fossil fuel etc. and formulate plans to deal with possible flooding of lowland areas and invent cost-effective ways to keep ourselves cooler during summer. It does not make sense to shut down coal mines and take away centuries-old livelihoods of miners nor force people to buy electric cars they cannot afford. Throwing soup at the painting of Mona Lisa or blocking traffic or giving up beef to raise the awareness of climate change are absurd ideas.

I am not in favour of pouring millions of dollars in aid to other countries without any accountability to help them fight climate change and holding glitzy international conferences. I am disappointed to see that almost every adverse atmospheric phenomenon is now blamed on climate change and the narrative has become political. Part of the reason is that governments are generously doling out grants to support research on climate change; naturally, scientists find it easier to get grants if they can somehow correlate their work with climate change; of course, they are all in agreement about the need to be proactive. I can perhaps explain my views with an analogy. Ever since I moved to Southern California 35 years ago, I have been hearing about a major earthquake (the “big one”) coming. In fact, we experience minor earthquakes almost weekly. There are theoretical models and predictions about how and when this big earthquake would take place affecting a metropolis of more than ten million people causing unthinkable damage.

However, the models cannot predict the event with any precision. So even though everyone knows that it can happen anytime we do not worry about it and have left ourselves at the mercy of Mother Nature. Reasonable precautions have been taken such as structural reinforcements of existing buildings and bridges, new building codes and designation of earthquake shelters; but I do not see efforts like national conferences, reduction of fracking and drilling, proposals of major geoengineering projects or millions of dollars being poured into earthquake research. There is no ban on living close to the fault lines either. My belief is that Mother Nature will do whatever Mother Nature wants to do. We cannot control her but only learn to adapt ourselves to her activities without preemptively sacrificing our lives, based on some computer models in the name of science.

(The writer, a physicist who worked in academia and industry, is a Bengali settled in America.)