Seasonal and decadal forecasting
We develop seasonal forecasting models for years, months or weeks ahead, designed ad-hoc for each client.
About the project
The study of atmospheric pollutants is essential above all because of their capacity to influence the tissues of living beings and cause harmful effects. With regard to exposure thresholds for setting a level of danger to the health of the population, the WHO sets limits depending on the pollutant: for PM2.5 it sets a maximum of 25 μg/m³ averaged over 24 h, PM10 50 μg/m³ averaged over 24 h, O₃ 100 μg/m³ averaged over 8 h, NO₂ 200 μg/m³ averaged over 1 h, SO₂ 500 μg/m³ averaged over 24 h. Prevention is therefore essential, especially for the most vulnerable population groups.
The objective of this research is to prevent the concentration of atmospheric pollutants and the effects they may have on the population in meteorological situations that lead to the exceedance of risk thresholds, through several sub-objectives: (1) to determine the analogous days that may cause an exceedance of a risk threshold; (2) to characterize the analogous days by classifying the most common scenarios that lead to risk scenarios; (3) weekly and seasonal projections with the possibility of addressing climate scales starting from the predicted global warming scenarios (associated with AR5) and equally being able to apply pollutant gas projection scenarios (SEI 2017).
The project is one of those carried out in 2018 within the framework of the “subsidies to third sector entities or non-governmental organizations that develop activities of general interest considered to be of social interest in the field of scientific and technical research of an environmental nature” by the Ministry for Ecological Transition.
Objectives
Activities carried out:
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Activity 1. Collection of PM2.5, PM10, O₃, NO₂ and SO₂ pollutant concentration data. Pollutant data were obtained from European, national, autonomic and municipal network data. These data make it possible to determine average pollution levels and the climatic incidence of pollution, as well as compliance with the thresholds set by the WHO.
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Activity 2. Data collection of surface meteorological variables (temperature, precipitation, humidity and wind). Surface meteorological data were collected from as many stations as possible and their quality was controlled, including a proper inhomogeneities test.
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Activity 3. Historical analysis of situations favorable to high pollutant concentration and selection of potential synoptic predictors. Based on an analog stratification, the most favorable scenarios for thermal inversion in the lower layers of the atmosphere that favor situations of high concentration of pollutants were determined, as well as the best predictors at synoptic scale to forecast these situations.
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Activity 4. Statistical prediction of meteorological variables and specific derived indicators. The pollutants were predicted based on the correlation of analogous scenarios for the key day. Long-term or climate-scale predictions were also made on the basis of the forcings predicted in AR5, evaluating the possible effects of climate change on pollutant concentrations.
Funded by
Ministry for the Ecological Transition and the Demographic Challenge through grants to third-sector entities or non-governmental organizations that carry out activities of general interest considered to be of social interest in the field of scientific and technical research and environmental protection under state jurisdiction. This research has been funded by the Ministry for the Ecological Transition and the Demographic Challenge but does not express its opinion.
