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OCHA-DAP / ds-raster-pipelines

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ERA5 download #8

Closed hannahker closed 2 months ago

hannahker commented 2 months ago

Adding ability to download and update all ERA5 monthly total precipitation reanalysis data from the CDS Beta API.

See Run ERA5 job on Databricks with all data in prod Azure container.

hannahker commented 2 months ago

Perhaps related to: https://github.com/ecmwf/cfgrib/issues/97

hannahker commented 2 months ago

Note that the output variable is total precipitation (tp), which is defined as:

This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of the grid box or larger. Convective precipitation is generated by the convection scheme in the IFS, which represents convection at spatial scales smaller than the grid box. This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This parameter is accumulated over a particular time period which depends on the data extracted. For the monthly averaged reanalysis and the monthly averaged ensemble members, the accumulation period is 1 day. For the monthly averaged reanalysis by hour of day, the accumulation period is 1 hour and for the monthly averaged ensemble members by hour of day, the accumulation period is 3 hours. The units of this parameter are depth in metres of water equivalent. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box.

Notably, this means that the value for each month is the modelled total precipitation for a given day in that month. To get the average monthly precipitation, you need to multiply by 30.