Latest version: V2.2 (released March 2, 2018)
Multi-Source Weighted-Ensemble Precipitation (MSWEP) is a new fully global historic precipitation dataset (1979–2017) with a 3‑hourly temporal and 0.1° spatial resolution.
Why use MSWEP?
- MSWEP takes advantage of the complementary strengths of gauge‑, satellite‑, and reanalysis-based data to provide reliable precipitation estimates over the entire globe.
- In two comprehensive large-scale evaluations, MSWEP performed best overall (Beck et al., 2017; Beck et al., 2019).
- Truly global coverage (including ocean areas) at 3‑hourly 0.1° resolution (other satellite-based datasets, such as TMPA 3B42, are limited to latitudes <50/60°).
- Consistent precipitation record from 1979 until the near present, enabling trend and drought assessments.
- Daily (in addition to monthly) gauge corrections using observations from ~77,000 stations across the globe.
- When applying the daily gauge corrections, MSWEP accounts for differences in gauge reporting times.
- Correction of systematic terrestrial precipitation biases using river discharge observations from 13,762 stations across the globe.
MSWEP has been part of two comprehensive evaluation studies. In the first, 22 gridded precipitation datasets were validated using observations from ~70,000 gauges and hydrological modeling for ~9000 catchments globally:
In the second, 26 precipitation datasets were evaluated using Stage-IV gauge-radar data for the CONUS:
- Beck, H. E., Pan, M., Roy, T., Weedon, G. P., Pappenberger, F., van Dijk, A. I. J. M., Huffman, G. J., Adler, R. F., and Wood, E. F.: Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS, , 2019.
MSWEP optimally merges a wide range of gauge, satellite, and reanalysis data to provide reliable precipitation estimates over the entire globe. See the following paper for a detailed description of the MSWEP V2 methodology:
- Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. M., van Dijk, A. I. J. M., McVicar, T. R., and Adler, R. F.: MSWEP V2 global 3‑hourly 0.1° precipitation: methodology and quantitative assessment, Bulletin of the American Meteorological Society, 100(3), 473 500, 2019.
The following paper describes the MSWEP V1 methodology:
- Beck, H.E., A.I.J.M. van Dijk, V. Levizzani, J. Schellekens, D.G. Miralles, B. Martens, A. de Roo: MSWEP: 3‑hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrology and Earth System Sciences .
The most important changes in V2 compared to V1 include: (i) the introduction of cumulative distribution function and precipitation frequency corrections, to account for spurious drizzle and attenuated peaks evident in V1; (ii) increasing spatial resolution from 0.25° to 0.1° to increase the local relevance of the precipitation estimates (especially important for high water-yield mountainous regions); (iii) the inclusion of ocean areas to enable oceanic studies and terrestrial hydrology studies for coastal areas and small islands; (iv) the addition of precipitation estimates derived from Gridded Satellite (GridSat) thermal infrared imagery for the pre-TRMM era to supplement the reanalysis and gauge data; (v) the use of a daily (rather than monthly) gauge correction scheme that accounts for regional differences in reporting times, to minimize timing mismatches when applying the daily gauge corrections; (vi) the use of a large database of daily gauge observations compiled from several sources to replace the 0.5° CPC Unified dataset; and (vii) extension of the data record to 2017 (MSWEP V1 finished in 2016).
See the technical documentation for the complete version history.
MSWEP is developed by Hylke Beck (Princeton University, Princeton, NJ, USA). The precipitation dataset developers are gratefully acknowledged for producing and making available their datasets. The work was supported through IPA support from the U.S. Army Corps of Engineers’ International Center for Integrated Water Resources Management (ICIWaRM), under the auspices of UNESCO. By using MSWEP in any publication you agree to cite Beck et al. (2019).