DOI: 10.48758/ufz.14923
title: [HICAM] climate projection; monthly SMI 1971-2098 in depth 0-200cm, full ensemble (88 members) cdf 1971 -2020, mHM, DE domain

description: Back up of the monthly Soil Moisture Index (SMI) simulated with mHM (https://mhm-ufz.org/) based on soil water content (SWC) in depth 0-200 cm at 0.015625deg spatial resolution, monthly time step 1971 -2098, using spatially diasaggregated and bias-adjusted simulations from EURO-CORDEX (Jacob et al, 2014) and Reklies-DE climate (Bülow et al, 2019). Further information on the SMI is found in Samaniego et al (2013) and the code in Samaniego et al (2022). The cumulative distribution function (cdf) of soil moisture (SM) for the SMI was calculated on the period 1971 -2020.

The look up table containing for the simulations and rejections of simulations due to quality controls are found in the separate data entry here: doi.org/10.48758/ufz.15153


Methodology and Dataset are presented in (non ISI listed):  
  
Marx, A., Rakovec, O., Boeing, F., Kelbling M., Thober S., Müller S., Samaniego, L. (2022). Towards high-resolution multi-model climate-hydrology indicators for Germany. In: Helmholtz Climate Initiative. Final report. https://www.helmholtz-klima.de/projekte/veroeffentlichungen  
  
Samaniego, L., Remke, T., Kevin S., Boeing, F., Rakovec, O., Marx, A., Thober. S. Müller, S. (2022). High-resolution bias-adjusted and disaggregated climate simulation ensemble. In: Helmholtz Climate Initiative. Final report. https://www.helmholtz-klima.de/projekte/veroeffentlichungen


References:

Samaniego, L., Kumar, R., & Zink, M. (2013). Implications of Parameter Uncertainty on Soil Moisture Drought Analysis in Germany. In Journal of Hydrometeorology (Vol. 14, Issue 1, pp. 47–68). American Meteorological Society. [https://doi.org/10.1175/jhm-d-12-075.1](https://doi.org/10.1175/jhm-d-12-075.1)

Samaniego, L., Kumar, R., Zink, M., Mai, J., Boeing, F., Shrestha, P.-K., Kaluza, M., Schäfer, D., and Thober, S.: The Soil Moisture Index – SMI program (2.0.5), Zenodo [code], https://doi.org/10.5281/zenodo.5842486, 2022.

mHM: The mesoscale Hydrological Model, GitHub [code], https: //github.com/mhm-ufz,

Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., ... , Yiou, P. (2014, April). EURO-CORDEX: new high-resolution climate change projections for European impact research. Regional Environmental Change, 14 (2), 563–578. Retrieved 2022-08-23, from http://link.springer.com/79410.1007/s10113-013-0499-2 doi: 10.1007/s10113-013-0499-2

Bülow, K., Huebener, H., Keuler, K., Menz, C., Pfeifer, S., Ramthun, H., Spekat, A., Steger, C., Teichmann, C., & Warrach-Sagi, K. (2019). User tailored results of a regional climate model ensemble to plan adaption to the changing climate in Germany. In Advances in Science and Research (Vol. 16, pp. 241–249). Copernicus GmbH. https://doi.org/10.5194/asr-16-241-2019 


Acknowledgments:


Parts of the work were conducted under the Helmholtz-Climate-Initiative (HI-CAM), which is funded by the Helmholtz Associations Initiative and Networking Fund. We express our gratitude for valuable cooperation during the HI-CAM project with Kevin Sieck (GERICS - Climate Service Center Germany) and Thomas Remke (formerly GERICS). We acknowledge the EURO-CORDEX community for making their RCM simulation results publicly available. The EURO-CORDEX initiative (https://euro-cordex.net) is a voluntary effort of many of the leading and most active institutions in the field of regional climate research in Europe. We also acknowledge the ReKliEs-De project (http://reklies.hlnug.de), funded by BMBF, for making their RCM simulation results publicly available. Also, we thank the UFZ high performance computing system EVE and their administrators, in particular Ben Langenberg, Toni Harzendorf, Christian Krause and Conrad Ostertag for their support in scientific computation. The authors are responsible for the content of this publication.