As a musician, I really enjoyed the collaboration with other musicians. Playing with multiple musicians, and bands, exploring new rhythms, musical genres, and places. That was not only exciting but also rewarding. The reward always came through learning from others. I honestly think, the more you play better you will be, the more you play with other musicians better we all will be.
Before the Covid pandemic, I had a band and we were playing music about climate change. The project was great and so much fun to do it. It was an audiovisual project where when playing live the songs would be synchronized with a video. The plan was going accordingly to the expectations but then Covid arrived with lockdowns, uncertainties, and only virtual music.
To fulfill my creative needs I started a concept album telling the story of how covid changed our lives (for better or worse). After a lot of work and effort (and of course fun!), finally, the 1st song of my Covid Chronicles album is out. I recorded during the pandemic and it is about the pandemic (kind of inception). I played all instruments and my friend Aybars recorded the drums. Because I really like the multimedia concept below you can check the video:
The second song is planned to be released in the summer so stay tuned!
Continuing my series of posts about making music inspired by videos/images I recorded previously based weather/climate events. This episode occurred when an unusual amount of snow felt during a short period of time this last winter. The therm unusual is used because this episode was unusual for the actual standards. The same amount of snow used to fall in the past and that was a normal event.
It’s been a while since my last post. Basically the struggle of any artist, be happy or make money!
Anyway, I have been experimenting and making music inspired by videos/images I recorded previously based weather/climate events. It is more or less like a little side project that will help me when creating the videos of the climate change prog rock opera.
This video I made when a series of storms hit the place where I live.
The reason I called this song I Believe In Gnomes, Santa Claus And The Weather Man is because sometimes I have the feeling that people believe more in gnomes than in the forecast of the weather man. They are not that bad and they do a really good work most of the time. Weather forecast is hard!
After a long break I am finally back. This is the first post of the “Weather Forecasting” posts. Roughly speaking, to forecast the weather, scientists use computer models to mimic Earth dynamics. These models are mathematical equations of the atmosphere and oceans. However, the Earth dynamics is a big complex system. On top of that some Earth natural systems have a chaotic behavior. But what is chaos? Summarizing the wikipedia definition:
Chaos is when the behavior of dynamical systems are highly sensitive to initial conditions. Thus, small differences in initial conditions (such as those due to rounding errors in numerical computation) yield widely diverging outcomes for such dynamical systems. Therefore, chaotic systems are predictable for a while and then appear to become random. In other words, the deterministic nature of these systems does not make them predictable.
Around 1960, the meteorologist Edward Lorenz (one of the fathers of chaos theory), was working on a set of differential equations describing convective processes in the atmosphere which were producing encouragingly realistic results. One day, he decided to enter data manually from a point part way through rather than waste time by starting the run over. He found that not long after the run had been restarted from this intermediate point, the forecast diverged and it was completely different. The reason behind, was the output data he used to restart the model. It had been rounded to 3 significant digits, while the computations were done to 6, an error of about 1%. With this unexpected results he discovered that the degree of numerical precision in the initial conditions provided to a numerical weather prediction (NWP) model affects the resulting forecast significantly after only a few days of forecast time (Lorenz 1963). A good example (also from wikipedia) of chaotic behavior is the double rod pendulum where the start of the pendulum from a slightly different initial condition would result in a completely different trajectory:
The Earth weather is one of the Earth natural systems with a chaotic behavior. Consequently, the use of different initial conditions in the atmospheric and oceans equations will lead to different final results. So why does not use the same initial condition always to forecast the weather and have the same results? The source of the errors in the forecasting is a more complex subject and I will explain in a post later. However if the Earth system is so unpredictable how come scientists can use computer models to reconstruct past and future climate? First it is necessary to explain the difference between weather and climate where the difference is a measure of time. Weather is what conditions of the atmosphere are over a short period of time, and climate is how the atmosphere “behaves” over relatively long periods of time. Weather is more difficult to predict and has more uncertainties than climate. An elegant demonstration of this difference can be seen in this short video from National Geographic. The astrophysicist and Cosmos host Neil deGrasse Tyson uses a dog walking to clarify the concept.