Possible error in rainfall data?



I was hoping to build an automated rainfall harvesting check on the top of the open access weatherninja rainfall data.

I downloaded the 2014 data for Gowerton, to compare it to a dataset I had from Natural Resouces Wales for the same area. Their data is trusted for this lcoation so it is a good baseline. There’s a large (35%+) difference, with renewables ninja underestimating the rainfall. https://github.com/cromlyngames/Cardiff_rain_storage/blob/master/Gowerton_2014_RainfallComparision.xlsx

There may be a difference of 1km between the sites but this would not explain the difference in rainfall. Any idea what the source of the difference might be and how I can correct for it?


Keeping public logs as I work through this:
Meera-2 laandsat documentation: https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/docs/

leads me to this:

Land Surface Precipitation in MERRA-2: https://journals.ametsoc.org/doi/pdf/10.1175/JCLI-D-16-0570.1

The precipitation corrections in MERRA-2 are refined from those used in MERRALand, with three main differences. First, and perhaps most importantly, the precipitation corrections in MERRA-2 were implemented in the coupled atmosphere–land reanalysis system. This allows the observed precipitation to impact, via evapotranspiration, the near-surface air temperature and humidity, hereby yielding a nearsurface meteorological dataset that is more selfconsistent than that of MERRA-Land. Second, the gauge-based precipitation corrections in MERRA-2 do not extend to the high latitudes. Third, over Africa MERRA-2 uses a (temporally and spatially) coarser precipitation data product that is based on satellite as well as gauge observations. The latter two changes were made because the sparse coverage and poor quality of the gauge-only precipitation product in Africa and at high latitudes had a detrimental impact on the MERRA-Land product (Mudryk et al. 2015, their Fig. 2; Reichle et al. 2017)

Still reading.


Dear P.
weather re-analysis models are subject to bias, and MERRA-2 is no exception.
Precipitation is especially challenging, as mentioned in the MERRA paper abstract (basis for MERRA-2), available at

Figure 4 in the MERRA-2 paper, available at https://journals.ametsoc.org/doi/10.1175/JCLI-D-16-0758.1 gives an indication of MERRA-2 model bias, and which regions of the world are most affected.

I think this bias is inherent to the MERRA-2 re-analysis model, and not easy to compensate. Still progress was already made by calibrating the model with real observations.

Hope that these additional references help,
Kind regards,
Hans Cappelle, Belgium