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Published September 11, 2019 | Version 1.3
Dataset Open

SM2RAIN-ASCAT (2007-June 2020): global daily satellite rainfall from ASCAT soil moisture

Description

SM2RAIN-ASCAT is a new global scale rainfall product obtained from ASCAT satellite soil moisture data through the SM2RAIN algorithm (Brocca et al., 2014; 2019). The SM2RAIN-ASCAT rainfall dataset (in mm/day) is provided over a regular grid at 0.1-degree sampling (3600x1801) on a global scale. The product represents the accumulated rainfall between the 00:00 and the 23:59 UTC of the indicated day. The SM2RAIN method was applied to the ASCAT soil moisture product (Wagner et al., 2013) for the period from January 2007 to 30 June 2020 (13.5 years), for version 1.3.

The rainfall dataset is provided in netCDF format. A total of 14 netCDF files, one per year, are provided. The quality flag provided with the dataset has been used to mask out low quality data, as well as the areas characterised by complex topographic, frozen soil, and presence of tropical forests. In addition to the daily accumulated rainfall value, also the rainfall noise (mm/day) is provided for every day.

Three new features of version 1.3:

  1. extension to the end of June 2020;
  2. data formatting over a 3D regular grid with spacing 0.1-degree;
  3. addition of the estimated rainfall noise (mm/day) for each day.

A GeoTIFF version of the dataset (v1.2) is available here (to be updated): https://zenodo.org/record/3520620

A sample dataset that can be used for testing SM2RAIN algorithm is available here: https://zenodo.org/record/2580285

Details on the dataset development and its assessment with ground and reanalysis observations are provided as:

Brocca, L., Filippucci, P., Hahn, S., Ciabatta, L., Massari, C., Camici, S., Schüller, L., Bojkov, B., Wagner, W. (2019). SM2RAIN-ASCAT (2007-2018): global daily satellite rainfall from ASCAT soil moisture. Earth System Science Data, 11, 1583–1601, doi:10.5194/essd-11-1583-2019. https://doi.org/10.5194/essd-11-1583-2019.

Simple Python and Matlab codes for the extraction of SM2RAIN-ASCAT rainfall at one and multiple station(s)\location(s) are available at: https://github.com/IRPIhydrology/SM2RAIN_ASCAT_reader

The SM2RAIN code in Python is available herehttps://github.com/IRPIhydrology/sm2rain
The SM2RAIN code in Matlab is available herehttps://github.com/IRPIhydrology/SM2RAIN_Matlab
The SM2RAIN code in R is available herehttps://github.com/IRPIhydrology/sm2rainR

 

Acknowledgements

  • EUMETSAT Global SM2RAIN project (contract n° EUM/CO/17/4600001981/BBo)
  • EUMETSAT “Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF)” CDOP 3 (EUM/C/85/16/DOC/15).

Notes

Dataset extended to June 2020. With respect to version 1.2 we have changed all files as we have added the estimation of the rainfall error (mm/day) and we have formatted the dataset over a 3D grid easier to be read from standard software.

Files

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Additional details

Related works

Is referenced by
10.5194/essd-2019-48 (DOI)

References

  • Brocca, L., Filippucci, P., Hahn, S., Ciabatta, L., Massari, C., Camici, S., Schüller, L., Bojkov, B., and Wagner, W. (2019). SM2RAIN-ASCAT (2007–2018): global daily satellite rainfall from ASCAT soil moisture, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-48, in review.
  • Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., Levizzani, V. (2014). Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research, 119(9), 5128-5141, doi:10.1002/2014JD021489.
  • Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S., Figa, J., de Rosnay, P., Jann, A., Schneider, S., Komma, J., Kubu, G., Brugger, K., Aubrecht, C., Zuger, J., Gangkofner, U., Kienberger, S., Brocca, L., Wang, Y., Bloeschl, G., Eitzinger, J., Steinnocher, K., Zeil, P., Rubel, F. (2013). The ASCAT Soil Moisture Product: A Review of its Specifications, Validation Results, and Emerging Applications. Meteorologische Zeitschrift, 22(1), 5-33, doi:10.1127/0941-2948/2013/0399.