Published July 8, 2021 | Version v2
Dataset Open

Soil moisture drought reconstruction across Europe since 1766

Creators

  • 1. UFZ
  • 2. Czech University of Life Sciences

Description

Data repository for: 

Rakovec, O., Samaniego, L., Hari, V., Markonis, Y., Moravec, V., Thober, S., Hanel, M., Kumar, R. (2022). The 2018-2020 multi-year drought sets a new benchmark in Europe. doi: 10.1029/2021EF002394

If you use this dataset in scientific publications, the aforementioned publication needs to be acknowledged.

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We provide a comprehensive spatio-temporal assessment of the drought hazard over Europe by benchmarking past exceptional events during the period from 1766-2020.

We provide gridded soil moisture simulations of the mesoscale Hydrologic Model (mHM; Samaniego et al., 2010; Kumar et al., 2013) in NetCDF format, transformed into a percentile-based monthly soil moisture index (SMI; Samaniego et al., 2013):

(1) Observation-based simulations of SMI from mHM: smi_dataset_obs_based.tar.gz: meteorologic forcings are based on 1766–2015 (Casty et al., 2007; ) and E-OBS v21 (Hofstra et al., 2009).

(2) Climate model-based simulations of SMI from mHM: smi_dataset_gcm_based.tar.gz This suite is based on five Coupled Model Intercomparison Project v5 (CMIP5) Global Climate Models (GCMs) (HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, GFDL-ESM2M and NorESM1-M) in the historical mode and under two future representative concentration pathways (RCP4.5 and RCP8.5), available from the ISI-MIP project (Hempel et al., 2013; Warszawski et al., 2014; Frieler et al., 2017)

mHM  code is available under: https://git.ufz.de/mhm/mhm, revision number: 8271b54

SMI code is available under: https://git.ufz.de/chs/progs/SMI, 

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Following variables are provided in the netcdf format:

float SMI(time, ncols, nrows) ; SMI:long_name = "soil moisture index" ;

int mSMIc(time, ncols, nrows) ; mSMIc:long_name = "monthly SMI indicator SMI < th" ;

int mDC(time, ncols, nrows) ; mDC:long_name = "consolidated cluster evolution" ;

Aggregated analysis of the soil moisture drought clusters is presented in ascii files:

results_ADM_yyyymm.txt

i - running index of clusters

c_Id - IDs of cluster

mStart - starting month 

mEnd - ending month 

aDD - average Drought Duration

aDA - average Drought Area

TDM - Total Drought Magnitude

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This study was done within the XEROS project (eXtreme EuRopean drOughtS: multimodel synthesis of past, present and future events), funded by the Deutsche Forschungsgemeinschaft (grant RA 3235/1‐1) and Czech Science Foundation (grant 19‐24089J) -- www.ufz.de/xeros

 

Files

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Additional details

References

  • Casty, C., Raible, C. C., Stocker, T. F., Wanner, H., & Luterbacher, J. (2007). A European pattern climatology 1766–2000. Climate Dynamics , 29 (7-8), 791– 805.
  • Frieler, K., Lange, S., Piontek, F., Reyer, C. P. O., Schewe, J., Warszawski, L., . . . Yamagata, Y. (2017). Assessing the impacts of 1.5 c global warm- ing – simulation protocol of the inter-sectoral impact model intercomparison project (isimip2b). Geoscientific Model Development , 10 (12), 4321–4345. doi: 10.5194/gmd-10-4321-2017
  • Hempel, S., Frieler, K., Warszawski, L., Schewe, J., & Piontek, F. (2013). A trend- preserving bias correction - the ISI-MIP approach. Earth System Dynamics , 4 (2), 219–236.
  • Hofstra, N., Haylock, M., New, M., & Jones, P. D. (2009). Testing E-OBS European high-resolution gridded data set of daily precipitation and surface temperature. Journal of Geophysical Research: Atmospheres , 114 (D21).
  • Kumar, R., Samaniego, L., & Attinger, S. (2013). Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and loca- tions. Water Resour. Res., 49 (1), 360–379. doi: 10.1029/2012WR012195
  • Samaniego, L., Kumar, R., & Attinger, S. (2010). Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res., 46 (W05523).
  • Samaniego, L., Kumar, R., & Zink, M. (2013). Implications of parameter uncertainty on soil moisture drought analysis in Germany. Journal of Hydrometeorology , 14 (1), 47–68.
  • Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., & Schewe, J. (2014, March). The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework. Proceedings of the National Academy of Sciences , 111 (9), 3228–3232. 11