Weather It Is (The First Rain Strikes Again)

 Good Afternoon:

Last week some might say they saw (or felt the pitter patter of) the first rain. Others might disagree, as the rain was very localized.  

However, a storm approaching from our north will draw moisture across the southern Mediterranean this Sunday afternoon. Combined with some upper level cold air, the moisture stream will lead to moderate to heavy rains across southern areas, including the Jerusalem area tonight and tomorrow (Monday). Floods will be possible in southern areas (https://www.timesofisrael.com/liveblog_entry/road-blocked-by-floods-near-eilat-reopens/).  Lighter rains should fall in northern areas.

As the week progresses, the storm will intensify as cold air continues to filter into it from the north.  There should be three waves of precipitation associated with it.  The first will arrive this Sunday night, while the second should arrive Wednesday.  The third, perhaps the strongest, could arrive late this week, but more likely early next week.  

This is a good start to our winter, after a very dry and warm October. I mention this because the seasonal forecast for our area is for well below normal precipitation (https://ims.gov.il/he/node/1673).  While this is cause for concern, one should keep in mind that last season the forecast was for above normal precipitation from October through December, and below normal precipitation from January through April.  In fact, we had very little rain until the last week in December, and finished the winter (and even spring season) well above normal.  

So, how can these forecasts be so off (as in wrong)?  The simple answer is that our forecasts often cannot predict very well beyond a week; that is: the variability in the forecasts (the global ensemble) becomes so large that there is no signal within the forecast ensemble that we can rely on. Or, there is no signal within the noise.

However, the idea in long range forecasts is that there are longer scale changes that are predictable, such that there are forecast deviations in the mean  temperatures and/or precipitation from weekly or monthly averages.  These longer scale changes are connected to "forcings" related to ocean currents and temperatures (like La Nina/El Nina) or changes in snow cover over the normally colder areas of the arctic and Siberia (https://www.aer.com/science-research/climate-weather/climate-dynamics/seasonal-weather-forecasts (https://www.aer.com/science-research/climate-weather/climate-dynamics/seasonal-weather-forecasts/).

Yet, there are so many teleconnections among the oceans and large scale atmospheric circulations (e.g., https://scied.ucar.edu/teleconnections-changes-weather-linked-together; https://journals.ametsoc.org/bams/article/91/3/381/59722/Teleconnections-in-the-Atmosphere-and-Oceans) that errors in the prediction of even one of them can lead to large errors in the seasonal forecasts (or even predictions for regional climate change) (e.g., https://journals.ametsoc.org/jcli/article/33/21/9145/353874/Tracing-North-Atlantic-Oscillation-Forecast-Errors; https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017RG000568). Perhaps, this is the simplest explanation for why many of our seasonal forecasts lack utility. 

There are other forecasts that can be inconveniently wrong. For instance, Hillary Clinton was forecast to win the 2016 election (https://www.nytimes.com/newsgraphics/2016/10/18/presidential-forecast-updates/newsletter.html).  Ironically, the pollsters appear to be making the same mistake as before. Then, pollsters said that "As a rule of thumb, we should expect Election Day polling averages to miss by as much as 3 to 4 points: Mrs. Clinton’s current lead in the national popular vote is around 6 to 7 points and growing."  And today, The New York Times notes that the margin of error is smaller than Vice President's lead in the polls (https://www.nytimes.com/2020/11/01/us/politics/biden-trump-poll-florida-pennsylvania-wisconsin.html?).  Yet, as noted in the aftermath of the election in 2016, "“It’s the overselling of precision,” said Dr. Pradeep Mutalik, a research scientist at the Yale Center for Medical Informatics) https://www.nytimes.com/2016/11/10/technology/the-data-said-clinton-would-win-why-you-shouldnt-have-believed-it.html).  How pollsters calculate the margin of error affects their models to predict the improbable, having deemed it impossible.

Of course, one might take further umbrage with predictions concerning the continuing saga of the Coronavirus.  Here, a top Israel professor predicted in April that the Coronavirus would disappear after 70 days (https://www.timesofisrael.com/top-israeli-prof-claims-simple-stats-show-virus-plays-itself-out-after-70-days/).   On the other hand, at the beginning of the pandemic, a top British scientist erroneously predicted: "Our estimates suggest the impact of the unfolding epidemic may be comparable to the major influenza pandemics of the twentieth"century(https://www.imperial.ac.uk/news/195217/coronavirus-fatality-rate-estimated-imperial-scientists/), where 50 million people may have died (https://www.cdc.gov/flu/pandemic-resources/1918-commemoration/1918-pandemic-history.htm).  Other earlier projections from the Imperial College London suggested that 2.2 million would die in the US by September, while the Center for Disease Control predicted 200,000 to 1.7 million (https://www.nytimes.com/2020/03/13/us/coronavirus-deaths-estimate.html). So far, the actual numbers in the US are about 230,000 and 1.2 million for the world.

So, you can see that forecasts or predictions are sometimes just wrong, or the range so large they can't be wrong.  All suffer from a combination of difficulties.   Both tomorrow's and next month's forecasts require an accurate assessment of the oceans (currents, temperatures), land (vegetation and ice) and atmosphere (temperature, humidity, etc), as well as programs to simulate the interactions between each of them.  Pollsters need to better estimate people's preferences, their desire to hide them, and their likelihood to act upon them (vote).  Epidemiologists must estimate infection rate, and how the infection rate may change due to mutations and people's behavior.  Bacteria and viruses can also become, through unforseen mutations, more or less infectious or deadly.

It's at times like this that we could really use a "Harry Seldon."https://en.wikipedia.org/wiki/Hari_Seldon#:~:text=Hari%20Seldon%20is%20a%20fictional,the%20future%20in%20probabilistic%20terms," a psychohistorian, whose ability was to predict the future in probabilistic terms, and suggest appropriate actions to prepare for the fall of the "Galactic Empire."

Were he to make an appearance, I would ask him: will we have a winter of plentiful rains, who will win the election, and when will the Coronavirus pandemic be behind us?  

My short answers: yes (or at least closer to normal than predicted), Trump, and next year.  However, you can ignore my predictions about Trump and the Coronavirus because I'm just guessing.  As for the seasonal forecast, it's unlikely that we would have such low total rain amounts, and maybe even less likely the seasonal models will be right in any year.

Barry Lynn