Implementation of a GNSS Meteorological model to the estimation of the Haines Index

L. FERNÁNDEZ; J. M. ARAGÓN PAZ; L. MENDOZA; A. MEZA

Viena

Congreso; EGU General Assembly 2017; 2017

European Geosciences Union

Wildfire indexes evaluate the risk of forest fire occurrences and the dangerousness of its large and erraticpropagation. In this context, the widely used Haines Index assesses the potential contribution of the atmosphere inforecasting and monitoring the behavior of the plume-dominated wildfires.The main goal of this study is the analysis of advantages in applying the GPT2w, an empirical model originallydeveloped for Global Navigation Satellite System (GNSS) Meteorology, to the estimation of the Haines Index. Tothis aim, a statistical analysis of the differences between this estimation and the real values from radiosondes wasperformed.The selected area comprises a region of South America between latitudes 15o S and 35o S. This area was chosendue to the availability of the radiosonde launches required for validation during the year of study (2011).Previously, for characterizing the expected regional performance of the Haines Index, the Climatology wasdeveloped by using data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysismodel (ERA Interim) for the period 2000-2011.Afterwards a statistical analysis of the differences between the index estimation from the application of theGPT2w with respect to the real index values, that is: Haines index calculated from radiosonde measurements wasperformed. Moreover, the additional estimation of the Haines Index by using multi-level data from ERA Interimat the same control stations was also provided.Because the GPT2w model is freely available, the analysis of the results discusses the advantages of using thisapproach where radiosonde launches are scarce. Likewise, strategies for improving the deficiencies of this estimateare also presented.