Rainfall Estimates on a Gridded Network (REGEN) - A global land-based gridded dataset of daily precipitation since 1950 — Australian Meteorological and Oceanographic Society
  1. Schedule
  2. 26(i). Big data in oceanography and meteorology: challenges, applications and data products
  3. Rainfall Estimates on a Gridded Network (REGEN) - A global land-based gridded dataset of daily precipitation since 1950

Rainfall Estimates on a Gridded Network (REGEN) - A global land-based gridded dataset of daily precipitation since 1950 (#138)

Steefan Contractor 1 2 , Lisa Alexander 1 3 , Markus Donat 1 3 4
  1. Climate Change Research Centre, UNSW Sydney, Sydney, NSW, Australia
  2. ARC Centre of Excellence for Climate System Science, UNSW Sydney, Sydney, NSW, Australia
  3. ARC Centre of Excellence for Climate Extremes, UNSW Sydney, Sydney, NSW, Australia
  4. Barcelona Supercomputing Centre, Barcelona, Spain

We present a new global land-based daily precipitation dataset from 1950 using an interpolated network of in situ data called Rainfall Estimates on a GriddEd Network - REGEN. We merged multiple archives of in situ data including two of the largest archives, the Global Historical Climatology Network - Daily (GHCN-Daily) hosted by National Centres of Environmental Information (NCEI), USA and one hosted by the Global Precipitation Climatology Centre (GPCC) operated by Deutscher Wetterdienst (DWD). This resulted in an unprecedented station density compared to existing datasets. The station timeseries were quality controlled using strict criteria and flagged values were removed. Remaining values were interpolated to create area average estimates of daily precipitation for global land areas on a 1°X1° latitude-longitude resolution. Besides the daily precipitation amounts, fields of standard deviation, Kriging error and number of stations are also provided. We also provide a quality mask based on these uncertainty measures. For those interested in a dataset with lower station network variability we also provide a related dataset based on a network of long-term stations which interpolates stations with a record length of at least 40 years. Here we document the development of the dataset and guidelines for best practices for users with regards to the two datasets.

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