A simple empirical method for estimating surface water vapour pressure using MODIS near-infrared channels: applications to northern Spain's Asturias region

In this article, we present a simple methodology for obtaining algorithms to estimate surface water vapour pressure (e(0)) over cloud-free land areas using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The algorithm obtained in this case is adapted to the particular climatic characteristics of the Asturias region, but the methodology can easily be extrapolated and used to obtain algorithms for other regions around the world. The proposed method estimates e(0) from a simple linear combination of the radiances of the MODIS near-infrared (NIR) channels more commonly applied to total precipitable water (W) estimations. Comparison between the e(0) data measured at the ground-based meteorological stations in Asturias (daily data from 2004) versus the values predicted using the proposed algorithm gives R-2=0.76 and residual standard error (RSE)=2.07hPa (16%). The algorithm was tested using the data from 2008 obtained in Asturias and in two sites outside of Asturias with similar latitudes and radiosonde observations (La Coruna and Santander). The resulting validation demonstrates that the algorithm gives good results in Asturias (root-mean-square deviation (RMSD)=2.50hPa (19%) and bias=1.26hPa, with R-2=0.65) and when La Coruna is included (R-2=0.61), but that its validity is decreased when Santander is also included (R-2=0.56). The possibility of obtaining e(0) from three global MODIS algorithms for W retrieval was also tested and compared to our algorithm. The results show that our algorithm gives better results than the International MODIS/Atmospheric InfraRed Sounder Processing Package (IMAPP) Water Vapour Near-Infrared (WVNIR) product and the Sobrino algorithm. The MODIS Total Precipitable Water (MOD05) product is worse than that obtained with our algorithm in Asturias (R-2=0.61 vs. R-2=0.65), but the two values are similar if the stations in La Coruna (R-2=0.60) and Santander (R-2=0.56) are included in the comparison. The dominant advantage of the novel algorithm proposed in this study is that it is simpler and can be produced quickly in real time.