High-resolution soil moisture forecasts for drought early warning in Germany: mHM-based soil moisture index reference dataset for Germany, January–September 2025 (7-day mean total soil column)(Najafi et al.) 0 17403

Project
POF3 - T53 - From models to predictions - Sub-seasonal Hydroclimatic Forecasting System - HS2S
Description

This dataset contains daily, high-resolution soil moisture index (SMI) data for Germany for the period 1 January–29 September 2025. It represents reference soil moisture conditions derived from total soil column moisture simulated by the mesoscale Hydrological Model (mHM). The subset covering 1 April–31 August 2025 was used to verify the HS2S forecasts in the associated study.

For the 2025 dataset, the SMI calculation uses a trailing 7-day mean of simulated total soil column moisture. The value assigned to each date therefore represents the average soil moisture for that date and the preceding six days. This temporal averaging is performed internally by the Fortran-based Computational Hydrosystems (CHS) SMI software as part of the SMI calculation and was not applied as a separate preprocessing step.

The SMI expresses the 7-day mean soil moisture at each model grid cell as a quantile relative to the historical soil moisture distribution for the corresponding time of year. The historical reference distribution is based on mHM simulations for 1975–2024. The SMI is dimensionless and ranges from 0 to 1, with low values indicating unusually dry conditions and high values indicating unusually wet conditions. For example, an SMI value of 0.2 indicates that the 7-day mean soil moisture is at approximately the 20th percentile of the 1975–2024 historical distribution for that time of year. In other words, approximately 20% of the historical values were equally low or lower.

The SMI was calculated using the Fortran-based CHS SMI software and methodology available at [https://git.ufz.de/chs/progs/SMI](https://git.ufz.de/chs/progs/SMI).

The underlying 2025 mHM simulations were forced by gridded meteorological observations from the German Weather Service (DWD). Precipitation forcing was obtained from the HYRAS gridded observational dataset, while the remaining station-based meteorological observations were spatially interpolated to the model grid using external-drift kriging (EDK).

This dataset serves as the 2025 reference SMI dataset (`SMI_reference`) for verification of the HS2S ensemble forecasts. It supports the calculation of forecast verification metrics, probabilistic drought analyses, figures, and tables presented in the associated manuscript, “High-resolution soil moisture forecasts for drought early warning in Germany.”
DOI
https://doi.org/10.48758/ufz.17403
Cite as (APA)
Najafi, H. (2026). High-resolution soil moisture forecasts for drought early warning in Germany: mHM-based soil moisture index reference dataset for Germany, January–September 2025 (7-day mean total soil column)(Najafi et al.) [Dataset]. Helmholtz-Centre for Environmental Research. https://doi.org/10.48758/UFZ.17403
Size
714,1 MB
License and Terms of Use
LICENSE and TERMS OF USE
Data quality
quality assured data
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Metadata Catalogues
Dublin Core
URI
https://www.ufz.de/record/dmp/archive/17403
DOI
10.48758/ufz.17403
Subject
soil moisture index (SMI)
Publication Date
27.07.2026
Type of data
dataset (structured data in a defined format)
Data quality
quality assured data
Status of data
derived data
Data format
netcdf
Creators
Najafi, Husain
Publisher
Helmholtz-Centre for Environmental Research
Rights holders
Helmholtz-Centre for Environmental Research
Contact
Husain Najafi (Husain.najafi@ufz.de)
Time or Period of creation
24.07.1987
Language of the content
English
Update policy
stored data will not be extended
Access permissions
free access