STRONG LAPSE CONDITION (LOOPING)
WEAK LAPSE CONDITION (CONING)
INVERSION CONDITION (FANNING)
Examples of Atmospheric Stability (attribution)
For the domain of Air Quality, just like for weather prediction, it is possible to define models used to predict the future set of atmospheric pollution. There are actually plenty of such models, often referred as Atmospheric Dispersion Modeling. And just like weather prediction, the same concept of accuracy analysis can be applied to Atmospheric pollution predictions. This article is the first of a series on Air Quality forecasting.
An observed forecast error may contain data errors of two kinds: (1) measurement errors in the data used to construct the forecast and (2) measurement error in the realized value. Data errors of the first kind will be a component of the true forecast errorError of type 2 are related to the dispersion model used for the forecast. Since different models are used for the different countries and continents (this is currently the case for the World Air Quality Index project), the accuracy analysis needs to be done for each of the model. So, to start with, this article will focus on the model used for the Asian continent. In later post, we will extend the analysis to more continents.
There are several ways of representing the accuracy, the most obvious one being a simple number representing percentage of forecast matching the actual observation. But because we do believe that graphic visualization are much more powerful than numbers, we prefer to present the superposed forecast/observation matching for several cities in Asia. The squares at the top are the empirical observations and the one at the bottom the foretasted values.
By checking all the graphs below, one can notice quite disappointing results for Guangzhou, Chengdu and South Korea... to the extent that the model in use for Asia could almost be disqualified for public usage. This is something that we will be writing in the second post of this series on Air Quality Forecasting.
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- AQI Scale: What do the colors and numbers mean?
- Using Statistical Distances for Real-time Sensor Networks Validation
- Kriging InterpolationRead or publish comments (they rely on Disqus)