Assessment of the potential of combined geodetic-based drought indices for studying climate change in Europe

Europe is undergoing increasingly extreme events, especially droughts that have become more frequent and severe. The observed conditions lead to water scarcity, agricultural impacts, and river flow issues, with projections indicating worsening conditions despite some regional variability. It is therefore crucial to find methods that can monitor drought conditions such as intensity, categories, and patterns, and that can assess the pacing of those changes over Europe. In recent years, there is an increasing application of geodetic techniques such as the Gravity Recovery and Climate Experiment (GRACE) and the Global Positioning System (GPS) in hydroclimatic research that enable monitoring of the continental water storage and Earth's displacement by observing the gravity field variations or the changes in the position of permanent stations, respectively. The recalculation of these changes into Drought Severity Index (DSI) provides a successful method for studying drought characteristics. However, limitations of both techniques, such as GRACE signal leakage and systematic errors of GPS, do not allow for an unambiguous assessment of drought. Thus, in our study, we overcome the limitations of both geodetic techniques by calculating a Multivariate DSI (MDSI) based on a combination of time series using the Frank copulas concept. We focus on emphasizing the potential of MDSI in describing drought characteristics compared to GRACE-DSI and GPS-DSI, as well as the sensitivity of DSIs to regional and local hydroclimatic and hydrometeorological changes recorded in Europe. In view of the sensitivity of both techniques to different temporal signals, we also take a step further by defining a new modified MDSI (mMDSI), which is the next step in climate change research. We divide GRACE-derived and GPS-observed displacement series into three temporal scales, i.e., short-term, seasonal, and long-term, which we then convert to DSI. The total mMDSI is defined as a combination of various temporal signals of GRACE-DSI and GPS-DSI. We perform spatial and temporal analyses to identify patterns of climate change, e.g., wetting/drying hotspots, and assess the reliability of mMDSI/MDSI by comparison with various meteorological and hydrological datasets. We prove that MDSI and mMDSI are key methods for decision-makers that may be applied in establishing preventive strategies to mitigate the effects of droughts in regions indicating ‘warning’ conditions.