## 1 Introduction
However, most satellite LST products are based on infra-red measurements and are therefore available under clear-sky conditions only. LST datasets are also likely to vary in terms of algorithms and input data or assumptions. The aim of this work is to analyze the sensitivity of drought assessment, via an improved VHI index as the one derived in Ref. [13], to the type LST dataset considered, namely the all-weather or the clear-sky ones. This is particularly relevant, as the use of a methodology based on VHI, and therefore on LST and on a vegetation index such as NDVI, is particularly suitable for the monitoring of drought over large areas using remote sensing data alone. For that purpose, we compare VHI derived with different LST datasets, namely the PU LST and the two clear-sky LST CDRs recently released by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM-SAF), both derived from Meteosat First (MFG) and Second (MSG) Generations [10; 33]. The Meteosat disk encompasses the African continent, southern Europe, and the northeast of Brazil. The Sahara Desert was not included in the analysis of drought conditions because of its persistent very arid character; in turn, the tropical rain forests and moister woody savannas found in equatorial central Africa are usually affected by very cloudy conditions and therefore fewer and less accurate satellite observations of the surface are available. Most of the remaining regions are however plagued by recurrent drought episodes: Iberia [34; 35], Euro- and African- Mediterranean region [36; 37; 38], eastern, southern, and the Sahel regions of Africa [39], and north-eastern Brazil [40; 41]. These are, consequently, regions of interest for this kind of analysis. Furthermore, drought frequency and severity are expected to increase due to climate change in regions like southern Europe and the Sahel [42; 43; 44; 45; 46; 47], making the region encompassed by the Meteosat disk a hotspot for future drought monitoring. The main objectives of this study are twofold: (1) to use the previously developed methodology to estimate contributions of thermal and vegetation stress to vegetation health [13] and (2) to understand whether, by using different LST CDRs--while preserving NDVI and SPEI--there are large differences from the optimum design of VHI, namely, if different weights should be attributed to the contributions of thermal stress and vegetation state in order to obtain an optimal vegetation health index. The behavior of contributions of thermal and vegetation stress for different biomes within the Meteosat disk is analyzed and three severe drought episodes, two in Iberia and one in Morocco are studied. This analysis may be viewed as a precursor for the development of a real-time product for drought monitoring using MSG and the future Meteosat Third Generation (MTG) instrument [48; 49]. The paper is organized as follows: in Section 2, the CDRs used in this study are presented and the methodology to estimate the VHI contributions is described; in Section 3, the optimum VCI/TCI weights for the computation of VHI derived using three different LST CDRs are intercompared and a biome analysis to assess dependencies of the contributions is performed; Section 4 includes the discussion of the results; and finally, Section 5 presents the overall conclusions and possible future work.