Open AccessDetermining temperature lapse rates over mountain slopes using vertically weighted regression: a case study from the Pyrenees
Author(s) -
Pagès Meritxell,
Miró Josep Ramon
Publication year - 2010
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.160
Subject(s) - mesoscale meteorology , peninsula , mm5 , climatology , downscaling , terrain , numerical weather prediction , range (aeronautics) , geology , advection , meteorology , multilinear map , geographically weighted regression , mountain range (options) , regression , orography , precipitation , prevailing winds , geography , cartography , statistics , mathematics , pure mathematics , materials science , physics , archaeology , financial economics , economics , composite material , thermodynamics
This study took place in the Pyrenees Range, in the northeastern Iberian Peninsula. The Pyrenees extend longitudinally, separating the Iberian Peninsula from the rest of Europe, and high peaks around 3000 m arise from deep valleys. As a mountain range it creates a barrier to advection, in this case from the north and south, and typical meteorological phenomena of mountainous areas occur within it (inversions, Foehn effect, extreme wind‐chill, snow storms). Thus, two specific valleys in Catalonia were considered, Val d'Aran and Cerdanya. In both valleys automatic weather stations (AWSs) are available at similar heights. Although these valleys are only 100 km apart, they have different climates. However, the main reason for developing the study was that Numerical Weather Prediction (NWP) has problems when forecasting temperatures in complex terrain areas, mainly in the valley floor in winter season. Firstly, different equations based on a multilinear regression were obtained for each weather station. Multilinear regression was considered in this case as the most suitable downscaling method and data used were provided by the AWSs and MM5 (PSU/NCAR mesoscale model) numerical weather prediction model outputs. These equations were obtained to set up a Geographically Weighted Regression (GWR) method, although this one was modified and changed to a Vertically Weighted Regression (VWR) in order to create vertical temperature profiles. Copyright © 2009 Royal Meteorological Society