High-resolution soil moisture forecasts for drought early warning in Germany

Abstract

Drought early warning increasingly relies on high-resolution monitoring, but the skill of daily soil moisture forecasts at lead times of 1–2 weeks driven by real-time meteorological ensembles has rarely been evaluated directly against an operational drought-monitoring framework. The Hydrological Sub-seasonal Forecasting System (HS2S) extends an established national drought-monitoring framework into high-resolution probabilistic soil moisture forecasts up to two weeks ahead for Germany at 0.015 625∘ resolution. We evaluated a daily-initialised HS2S configuration using the 51-member real-time forecast ensemble from the European Centre for Medium-Range Weather Forecasts during the exceptionally dry spring and summer of 2025 against the operational, model-based German Drought Monitor (GDM), generated within the same mesoscale Hydrologic Model (mHM) framework using observation-based meteorological forcing. The assessment combined drought onset/recovery transition diagnostics with probabilistic (Brier skill score) and categorical verification against an initialised two-state Markov persistence benchmark, and continuous verification against an mHM soil moisture climatology. HS2S reproduced the timing and mean magnitude of GDM-indicated drought onset and recovery. It showed positive probabilistic skill relative to the initialised Markov benchmark and positive continuous skill relative to the 1950–2017 mHM climatology at both lead times. For moderate drought ( SMI<0.20), the critical success index improved by 15.0 and 15.5 percentage points at lead weeks 1 and 2, respectively. The probability of detection of GDM-indicated drought was 95% and 89% at the same lead times. Given HS2S and the GDM share the same mHM–Soil Moisture Index framework and initial states, the verification is model-consistent and evaluates skill in anticipating the GDM-indicated drought state rather than validating absolute soil moisture accuracy. The added value of real-time meteorological forecasts relative to historical meteorological sequences was not assessed. Within this operationally relevant framework, HS2S showed forecast skill up to two weeks ahead during the 2025 drought, highlighting the potential of high-resolution probabilistic soil moisture forecasts to complement national drought monitoring with forward-looking information.