What can we learn from weather apps user complaints?
Authors: Lorente Plazas Raquel , Molina Marcos , Sanchez Juan , Palacion-Peña Laura , Ballester Guillermo 
Published: June 2021

&lt;p&gt;Meteored&amp;#8217;s goal is to provide a weather forecast to an heterogeneous audience around the world through its websites and mobile apps.&amp;#160; Although the meteorological information is available through several products such as radar, satellite or weather field maps, most of the views are focused on checking the forecast for a specific location. Our weather forecast is built on the HRES model from ECWMF, which is post processed, spatially interpolated to the interested coordinates,&amp;#160; and, finally, summarized in several weather symbols. If any user doesn&amp;#8217;t agree with the symbol that represents the forecast, she/he can select which symbol better represents its weather perception.&lt;/p&gt;&lt;p&gt;Using this simplification to validate forecast entails several challenges: 1) Spatial representativeness; there aren&amp;#8217;t weather stations at each location where users demand to validate, 2) timing; sometimes there is lack of concurrency between a weather phenomenon and the user weather check,&amp;#160; 3) user perception; same symbol can represent different weather for different users, and 4)&amp;#160; population density; most of the user complaints are focused on the most populated regions but this doesn't mean the performance is worse there.&lt;/p&gt;&lt;p&gt;Last year more than 374000 symbol suggestions were recorded from worldwide users, mainly from Europe and Southamerica. The percentage of complaints were 39% cloudy, 24% rainy, 21% suny, 8% storm, 5% snow and 3 % foggy. 16 % of the complaints happen when a cloudy symbol is shown but the user suggests a rainy symbol. Temporal series show more feedback during summer and slightly lower during March (maybe due to the pandemic). Complaints about snow significantly increased due to the historical event in Spain during January. From weather feedback, the straightforward question is: why most frequent complaining is about cloudiness? We can find several answers: there is an important error in the weather modelling, there is an error in the symbol representation, it is a frequent meteorology event or it is one of the most relevant in users daily life.&lt;/p&gt;&lt;p&gt;In order to understand how reliable the user&amp;#8217;s feedback is, our forecast is compared against almost 10000 SYNOP observations, assessing 2 m temperature, 10 m wind speed, precipitation, fog and also, symbols. Preliminary results show a pronounced dependence of the bias with the orography with larger errors over some islands and over main mountain systems. This spatial variability for bias is smoothed in Meteored forecast due to biquadratic interpolation. However, the Meteored forecast has a diurnal cycle bias error with higher temperatures during the daytime and lower temperature at nighttime due to the temporal interpolation approach.&amp;#160;&amp;#160;Regarding to the weather symbols validation is difficult to extract conclusion since failures and hits are hetereogenously distributed. In addition,&amp;#160; most discrepancies are related to fog although it has a low percentage of complaints.&amp;#160;&lt;/p&gt;