Yandex.Meteum - technology without technology. Marketing accurate to area

 3r3307. 3r3-31. Yandex. Meteum - technology without technology. Marketing accurate to the area
 3r3307. It has been exactly 3 years since the launch of the Yandex.Meteum service, which, according to the developers, gives the highest-quality forecasts among all the forecast sites. It's time to take stock. Is the new product of Yandex really revolutionary or is it all just marketing stuff? And as a team of scientists from the Hydrometeorological Center of Russia, we managed to bypass Yandex and create a truly high-quality forecast.
 3r3307.
 3r3307. Yandex.Meteum - technology without technology. Marketing accurate to area
 3r3307.
 3r3307. To begin, I will introduce myself. My name is Ilya Vinshtein, I am an amateur weather forecaster from Kurgan. I am engaged in meteorology for 14 years. I administer my regional project 3r313. "Weather 45"
, gave several lectures for the scientific and educational project "The Smoking Gutenberg."
 3r3307. the beginning of 2016 , but at that time I had a very small amount of data to make unambiguous conclusions. I mainly criticized the information campaign that Yandex launched. If at the very beginning they used the slogan “Forecast with accuracy to the house”, then they changed it to “Forecast with accuracy to the region”.
 3r3307.
 3r3307. In what form did the birth of Meteum take place? There were a lot of publications in the media, several publications on Habré, then short tutorial videos went on to explain the creation of the first predictive service based on the neural network. Creation of the Meteum came at a time when neural networks were very popular, and the media presented them as a panacea that could solve many problems of humanity.
 3r3307.
 3r3307. In the wake of the general neuroauge in Yandex decided to update its main meteorological section. Regular updating of the design and adding new functions is not an option, and the main goal of the update is to attract new audiences from competitors. The only way was to change the paradigm of service perception. Not just a weather section, but a completely new service that can predict the weather better than all other competitors. Not just “Yandex. Weather, ”and“ Yandex. Meteum ”is a system capable of issuing a forecast accurate to the home or district.
 3r3307.
 3r3307. The problem is that the final product is difficult to evaluate and receive feedback. Who will check the quality of forecasts? How will the feedback from users be evaluated? In our case, the consumer is unable to assess the quality of the final product, so he can “vparit”, anything can be done. Users of all forecast sites use this trick.
 3r3307.
 3r3307. Therefore, the entire information campaign on the launch of Meteum looks like an anti-scientific farce. For all 3 years, Yandex has not provided us with any objective figures. We have not seen a single report on the justification.
 3r3307.
 3r3307. All numbers came down to this:
 3r3307.
“According to our own estimates (alas, there are no independent meters in this area yet), for today our weather forecast is more accurate than all our known competitors. For example, the temperature forecast for 24 hours is mistaken for us by 35% less than the nearest competitor. ”
 3r3307. This is an absolute lie. I will explain why. If the year was 196? then this statement was absolutely fair, but now the short-term forecasts have already reached a certain ceiling. The struggle goes for interest and even a few tenths of a percent. For example, 3r3355. According to the Hydrometeorological Center of Russia
the accuracy of the forecast of air temperature in Russia in 2017 per day was 93%. We are talking about those forecasts, which were issued by forecasters of local weather centers. For predictive sites and computer models, accuracy varies from 85% to 95%. No 35% here and there can not be!
 3r3307.
 3r3307. How does this happen in the world of science?
 3r3307.
 3r3307. Suppose that Yandex managed to create a revolutionary product that truly bypasses all competitors. Introduce the world to this technology. Let the Yandex team show the world what they managed to create. Why not start with an article in a scientific journal? I understand that it may not be worth disclosing all the cards, because the product, in fact, has a commercial component, there is nothing wrong with that, but only if this product really works.
 3r3307.
 3r3307. Any scientific method of forecasting passes the testing phase. Usually experimental hares are archival data. In some cases, it is necessary to collect data for a year or several years, and only then publish the article. After this, the forecast is compared with the actual weather station reports. Prognostic fields are related to actual ones. The mass of parameters is calculated: the arithmetic mean temperature error, the average absolute temperature error, the relative error and justification in percent. Then, based on the results of operational tests, a special methodical commission makes a decision to recommend or refuse the use of this forecast method.
 3r3307.
 3r3307. And now a question for the developers of Yandex. Where is this data? Where are these articles and studies? “We have the most accurate predictions, believe us,” say in Yandex. Nothing to show. Nothing to brag about.
 3r3307.
 3r3307.  3r3307.
 3r3307. We have the numbers, but we will not show them to you. You have no documents.
 3r3307.
 3r3307. Ensemble and multi-model predictions 3-3-33290.
 3r3307.
 3r3307. Recently, ensemble, multi-model and complex forecasts have won great popularity among weather forecasters. What does it mean? First, a little theory. The main source of all forecasts are computer models. Programs that simulate the entire atmosphere of the Earth, starting from the soil and ending with the upper layers of the stratosphere. The main food for the models are satellite data in all visible and invisible spectral ranges. The data of ground stations now do not have such a strong influence on the quality of the forecast. If we exclude a layer of weather stations from models, the quality will fall by 7%, and if we exclude satellite data, then by 35-40%. There are 11 global models in the world and a dozen more regional ones.
 3r3307.
 3r3307. Computer models are very, very complex! Not every state is able to create its own qualitative model. For example, the domestic model PLAV occupies the 8th position in the ranking of world models. It exists, but almost never used.
 3r3307.
 3r3307. For this reason, most sites and applications use only 2-3 models. Everything else is a matter of internal processing and interpretation of data. For example, now the European Medium-Term Weather Prediction Model (ECMWF) is the best model. This model uses Foreca, intellicast and Gismeteo. BUT! As I said, the processing of forecasts is reduced to internal patterns that are engaged in "grinding" the raw files of the model. Gismeteo makes it worst of all, and Intelicast makes it better. Next will be the numbers confirming this.
 3r3307.
 3r3307. Okay, we figured it out. One run of a computer model is in its pure form a deterministic forecast on an “as is” basis. The main problem of deterministic forecasts is errors in the initial data, which lead to the butterfly effect. The smallest initial disturbances lead to huge errors in the medium term. To solve this problem, scientists have developed ensemble forecasts . Imagine the usual deterministic forecast. An artificial error is introduced into this prediction using a pseudo-random number generator.
 3r3307.
 3r3307. 3r3116.
 3r3307. Ensemble forecast. American model GFS. 20 members.
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 3r3307. And this is done another 20 or 50 times. Then a graph is drawn up, where you can see how sensitive the forecast is to errors in the initial data. If the deterministic forecast gives a warming after 10 days, and 20 ensemble members go down, that is, they give a cold snap, then the deterministic forecast for this period is erroneous.
 3r3307.
 3r3307. But scientists went even further. They began to synchronize deterministic forecasts and create 3r3129. multi-model forecasts
when the forecast is not based on one model, but a dozen at once.
 3r3307.
 3r3307.  3r3307. Multi-model forecast for Moscow on the site meteoblue. 11 models
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 3r3307. For example, 7 models give precipitation after 5 days, and 3 predict dry weather. Consequently, the probability of precipitation is 70%. Together, it is recommended to watch more and ensemble forecast.
 3r3307. And now we are getting to the point. How did the weather center manage to bypass Yandex?
 3r3307.
 3r3307. 3r33150. [b] Comprehensive Forecast

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 3r3307. In 201? the head of the hydrodynamic short-term forecasts of the Hydrometeorological Center of Russia and meteorologist Honored Alexei Bagrov, together with his team, developed a simple, but in principle, 3-33158. A new statistical processing scheme for raw forecast data 3r3-33267. . It was published in the journal "Meteorology and Hydrology" in an article entitled "Comprehensive forecast of surface meteorological variables."
 3r3307.
 3r3307. The essence of the technique is simple, but this is its superiority. Comprehensive forecast obtained by statistical processing of the results of the included models. At the same time, for the air temperature, wind and dew point, an archive of forecasts for the previous 20 days is used for the relevant models and actual data at the station, and for precipitation a similar archive is for one year. The calculation is carried out separately for each station and for each forecast lead time.
 3r3307.
 3r3307. If it is even simpler, then Bagrov proposes to perform a statistical adjustment of the forecasts of the best models based on the actual data of the local weather station. 3r3168. The technique is described in detail in article
itself. . Here I will focus on some highlights. The calculation of the maximum and minimum temperature is performed taking into account the error for the last 5 or 3 days. For example, over the past 5 days, our models have lowered the temperature by an average of 2 degrees, so we need to include this error in the last forecast and stabilize the forecast to the most likely value. Thus, the forecast itself automatically adjusts itself, based on previous deviations in the direction of overestimation or understatement.
 3r3307.
 3r3307. 4 year forecast was in the testing stage. In September 201? test results were published in the journal 3r3174. "Russian Meteorology and Hydrology"
. Briefly results of the study 3r3176.
announced here. . I will note that for all 4 years the forecast was published on the website of the methodical cabinet of the Hydrometeorological Center of Russia. It was calculated for 224 cities of Russia. Every month was a report of acquittal. They continue to go to this day.
 3r3307.
 3r3307. Modest and quiet - created the best forecast 3r-3290.
 3r3307.
 3r3307. The Hydrometeorological Center of Russia did something that nobody else could do. They automatically collected forecasts of 7 different forecast sites and analyzed their accuracy. Below are the data for 1.5 years - from January 2016 to June 2017 for Moscow, St. Petersburg and Yakutsk.
 3r3307.
 3r3307. 3r3192.
 3r3307. The average absolute error of the forecasts of the minimum (a) and maximum (b) temperature by city: Moscow, St. Petersburg, Yakutsk for the period January ? 2016 - June 3? 2017 Site forecasts: 1 - Meteoinfo.ru; 2 - Gismeteo.ru; 3 - Fobos (meteovesti.ru); 4 - Rp5.ru; 5 - Yandex.ru; 6 - Intellicast.com; 7 - Complex forecast by Bagrov.
 3r3307.
 3r3307. We got to the bottom. From the data it can be seen that on the first day of the daily temperature, Yandex bypasses 3 resources at once: meteoinfo, intellicast and the integrated forecast of Bagrov. The latter shows the lowest error for 1-2 days. For 3-4 days Intellicast and a comprehensive forecast lead. Yandex only on 3 positions.
 3r3307.
 3r3307. Please note that the most popular Gismeteo in Runet is not that precise. On the first day, its average error of 2 degrees is a lot. The ranking leader is meteovesti.ru
 3r3307.
 3r3307. Do not think that fresh data is no more. At the beginning of 201? a section 3-33209 appeared on the website of the methodological cabinet of the Hydrometeorological Center of Russia. “Evaluating Forecasts on Various Web Sites” 3-333267. . The section publishes data for 47 cities both individually and together.
 3r3307.
 3r3307. Many may say that this is outdated data, but there is already a fresh report of justification for October. We study it. Take a sample of 27 cities for ETR.
 3r3307.
 3r3307.  3r3307.
 3r3307. The forecast of daytime temperature at Yandex for one day is comparable to the accuracy of intellicast and a comprehensive forecast. For the next 2-5 days, intellicast slightly bypasses Yandex. With the forecast of night temperature at Meteum, everything is somewhat worse. On the first day, it goes around 3 sites: meteoinfo, intellicast and a comprehensive forecast. The next day the trend continues. On the 6th day Yandex overtakes intellicast and meteoinfo.
 3r3307.
 3r3307. For the Asian territory, the distribution is approximately the same. In almost all cases, Yandex bypasses the meteoinfo, intellicast and complex troika. Many have noticed that the official website of the Meteoinfo Hydrometeorology Center provides good accuracy. Yes it is. Now the site uses an independent statistical scheme for processing model data called 3r33228. REP (calculation of the elements of the weather)
. This scheme is not bad, but somewhat worse than a complex forecast. In the winter, she doesn’t predict good nightly cooling. I draw your attention that all these data processing schemes were invented long before the creation of a propia Yandex. Meteum.
 3r3307.
 3r3307. [b] Problems display and display

 3r3307.
 3r3307. It is not enough to create a qualitative forecast, it is necessary to learn how to adequately display it for the average person. When a user visits a weather site, he first looks at the forecast for 10 days, getting a general picture of the temperature change. But if you dig deeper, looking at the course of temperature, then many nuances will open. For example, the site indicates that the day will be +15 degrees, but then you open the temperature course and understand that these +15 will be at night, and during the day the temperature will be lower! This situation is called reverse temperature when it is warmer at night than during the day. The problem of outputting the maximum and minimum temperatures here is that the min and max values ​​are captured from the entire time series, not dividing day and night. From the point of view of the man in the street - this is a hoax. This sin all sites. The maximum temperature is usually fixed from 08 to 20 hours, depending on the season, the synoptic situation and the coordinates of the weather station. The minimum is noted from 20 to 08 hours, again, depending on the season and weather conditions. This is called a meteorological day. For example, the main meteorological station Moscow on VDNH sends the maximum temperature at 21 o'clock, and the minimum at 9 o'clock.
 3r3307. Below, I have brought situations of an atypical temperature variation, when it is important to capture the maximum and minimum temperature not from the entire time series, but at strictly fixed intervals. If conditions are not met, thenThe benefactor will be deceived, even despite the qualitative forecast.
 3r3307.
 3r3307.  3r3307.
 3r3307. Another problem is that a couple of years ago, Yandex began issuing climate data for a long-term forecast, which is not entirely correct. In Yandex, it was decided to use the raw CFSR (NCEP) computer reanalysis files for the last 7 years, creating a small climate sample. Now they have switched to the averaging period of 10 years, which does not change the situation. Also on the site appeared the parameter "Probability of precipitation", which was similarly calculated over the past 10 years based on computer reanalysis, but there is a serious problem. Computer reanalysis very poorly simulates convective rainfall and light snowfall in winter, so Yandex could issue a 0% probability, and according to the weather station it was 50%, just because the weather station has a precipitation meter that captures real precipitation, but not virtual . Therefore, it is more correct to average the data on the weather station, and not on computer reanalysis. I wrote to Yandex and received a response: “We added it to the list of suggestions of our users. Our specialists are always acquainted with these ideas when they prepare any changes in the service, and try, if possible, to take them into account. ” After 6 months, nothing has changed.
 3r3307.
 3r3307.  3r3307. Stay alive (c)
 3r3307.
 3r3307. I also suggested that Yandex, instead of averaging data over 10 years, use forecasts of the long-term climate model CFSv2. It is updated 4 times a day and considers the forecast for 9 months ahead. Of course, we are talking about getting a decade or average monthly data. But this is a real forecast, not historical information. For example, now the model shows that November in the European part of Russia will be warm and dry .
 3r3307. It was especially amusing to watch how Yandex epically rolled out prognostic maps, although at that time earth.nullschool.net, windytv.com and ventusky.com already existed. These services provide many times more information on various models. They wrote in Yandex that the main difference from them is that they have higher accuracy. Oh well.
 3r3307.
 3r3307.  3r3307.
 3r3307. The problem of night cooling
 3r3307.
 3r3307. Now in synoptic meteorology there is still an urgent issue with the prediction of night temperature in the conditions of anticyclonic air cooling. What is the problem? The problem is that computer models almost always in such a synoptic situation overestimate the temperature. For example, in Kurgan, according to most forecasts, at night the temperature will drop to -30 degrees: it will be clear, the pressure will rise, and the core of the anticyclone will pass over the region. Ideal conditions for cooling. But in fact, the minimum can drop to -35 - 37 degrees! When Yandex launched Meteum, I thought that finally it would be possible to solve this problem. But already that winter, Yandex continues to inflate the night temperature in the conditions of cooling. At the moment there are only 2 models in the world that can adequately calculate this temperature. The first is the Canadian GEM model. The second is the North American NAEFS. In other synoptic situations, these models do not show anything outstanding, so my task as a forecaster is to include these models in the forecast at the right time, and then at the right time to exclude them from the forecast. Even with the cooling cope complex forecast Bagrova, just due to statistical adjustments based on the local weather station.
 3r3307.
 3r3307. Conclusion
 3r3307.
 3r3307. The data obtained allows us to say with confidence that the temperature forecast of Yandex using the “Meteum” technology does not show any exceptional results compared to the well-established forecasting services. On the contrary, Yandex is inferior in quality to such resources as intellicast, meteoinfo and Bagrov’s integrated forecast published on the website of the methodical cabinet of the Hydrometeorological Center of Russia. The worst weather services can be called Gismeteo and meteovesti.ru
 3r3307. There is science, and there is marketing. One goal is to achieve a result, in our case, high precision. In the other, the goal is to gain and receive an imaginary and bloated achievement that does not carry any practical significance for the average man. Yes, the Hydrometeorological Center is a state organization that does not have such advertising budgets and opportunities as Yandex has, but the main thing is that there are still people there who can not create money, but science. 3r3303. 3r3307. 3r3307. 3r33300. ! function (e) {function t (t, n) {if (! (n in e)) {for (var r, a = e.document, i = a.scripts, o = i.length; o-- ;) if (-1! == i[o].src.indexOf (t)) {r = i[o]; break} if (! r) {r = a.createElement ("script"), r.type = "text /jаvascript", r.async =! ? r.defer =! ? r.src = t, r.charset = "UTF-8"; var d = function () {var e = a.getElementsByTagName ("script")[0]; e. ): d ()}}} t ("//mediator.mail.ru/script/2820404/"""_mediator") () (); 3r33333. 3r3307. 3r3303. 3r3307. 3r3307. 3r3307. 3r3307.
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