ERA5-Land data documentation

Introduction

Here we document the ERA5-Land dataset, which, eventually, will cover the same period as ERA5, January 1950 to near real time (NRT). ERA5-Land data released so far covers the period from 2001 to 2-3 months before the present. The period 1981-2000 will be released in Autumn 2019, whereas the back-extension from 1950 will start production in late 2019 with the release planned for Q2 2020. In addition, the facility to deliver timely updates is being implemented and it will be made available shortly. ERA5-Land timely updates (hereafter called ERA5-LandT) will be synchronized with the timely updates of the ERA5 climate reanalysis (ERA5T).

ERA5-Land is a replay of the land component of the ERA5 climate reanalysis, but with a series of improvements making it more accurate for all types of land applications. In particular, ERA5-Land runs at enhanced resolution (9 km vs 31 km in ERA5). The temporal frequency of the output is hourly and the fields are masked for all oceans, making them lighter to handle. Click this link here for comparison of the ERA5-Land features against other ECMWF reanalyses.

ERA5-Land is produced under a single simulation, without coupling to the atmospheric module of the ECMWF's Integrated Forecasting System (IFS) or to the ocean wave model of the IFS. It runs without data assimilation, making it computationally affordable for relatively quick updates. For example, if significant improvements of the land surface model are implemented, the whole or part of the dataset can be reprocessed in a relatively short period. Also, updates are possible in case improved auxiliary datasets are used as input for the production. Observations indirectly influence the simulation through the atmospheric forcing of ERA5. This forcing drives the ERA5-Land single simulation and it has been obtained by assimilating observations through a 4D-VAR data assimilation system and a Simplified Extended Kalman Filter. 

The core of ERA5-Land is the Tiled ECMWF Scheme for Surface Exchanges over Land incorporating land surface hydrology (H-TESSEL). It uses version CY45R1 of the IFS.

Currently, ERA5-Land dataset contains only one (9 km) high resolution realisation (HRES). Uncertainty information can currently be used from the reduced resolution ten member ensemble (EDA) of ERA5. The data are available at a sub-daily and monthly frequencies. For convention and consistency with the previous ERA-Interim/Land dataset, the data parameters are labelled as analyses and short (24 hour) forecasts initialised once daily from analyses at 00 UTC. Accumulation parameters are only available from the forecasts.

Currently, the data can only be downloaded on a regular latitude/longitude grid of 0.1°x0.1° via the CDS catalogue. In the near future the data will be made available in the native grid.

Land Surface Model 

H-TESSEL is the land surface model that is the basis of ERA5-Land. The H-TESSEL version used in the production of ERA5-Land corresponds to that of the IFS model documentation CY45R1.

Data organisation and access

The data are archived in the ECMWF data archive (MARS) and the data have been copied to the Climate Data Store (CDS). The data should be downloaded using the CDS catalogue or the CDS API, which can obtain data from the CDS copy or from MARS (Member State users can access the data using MARS directly, in the usual manner). Documentation on how to use the CDS API to download ERA5-Land data can be found here. The installation and downloading steps are similar to those of ERA5.

A couple of downloading examples to extract the data using the CDS API are given below:

#!/usr/bin/env python
import cdsapi

c = cdsapi.Client()
c.retrieve(
    'reanalysis-era5-land',
    {
        'format':'grib',
        'time':[
            '00:00','01:00','02:00',
            '03:00','04:00','05:00',
            '06:00','07:00','08:00',
            '09:00','10:00','11:00',
            '12:00','13:00','14:00',
            '15:00','16:00','17:00',
            '18:00','19:00','20:00',
            '21:00','22:00','23:00'
        ],
        'day':'01',
        'month':'01',
        'year':'2013',
        'variable':'snow_depth_water_equivalent',
    },
    'snow_20130101_era5land.grib')

#!/usr/bin/env python
import cdsapi

c = cdsapi.Client()

c.retrieve(
    'reanalysis-era5-land',
    {
        'variable':'runoff',
        'year':'2013'
        'month':'01',
        'day':'01',
        'time':'12:00',
        'format':'grib'
    },
    'runoff_00-12_20130101_era5land.grib')

Convention used in MARS: the date and time of the data is specified with three MARS keywords, 'date', 'time' and 'step'. For parameters labelled as analyses (see list of parameters), step=0 hours so that date and time specify the analysis time. All forecasts start at 00UTC (time=00 hours), and for parameters labelled as forecasts (see list of parameters), date specifies the forecast start day and step specifies the number of hours since the start of the forecast, with a maximum of step=24 hours. The combination of date, time and forecast step defines the validity date/time. For analyses, the validity date/time is equal to the analysis date/time.

Convention used in the CDS: 'analyses' are provided if available for a particular parameter, otherwise forecasts are provided. The date and time of the data is specified using the validity date/time, so step does not need to be specified. For parameters labelled as forecasts in MARS, steps between 1 and 24 hours have been used to provide data for all the validity times within 24 hours, see Table 0 below.

Table 0: the mapping, for forecasts, between MARS date, time and step and the CDS date and time

Spatial grid

The ERA5-Land HRES dataset has been produced at a resolution of 9 km, (~0.08°) and in a (octahedral) reduced Gaussian grid (represented as TCo1279). Currently, the uncertainty of the fields is to be obtained from the ERA5 EDA dataset, which has a resolution of 62km (~0.56°).

The article "Model grid box and time step" might be useful.

Temporal frequency

For sub-daily data for the HRES (stream=oper) the parameters labelled as analyses (type=an) are available hourly. The once daily short forecasts, run from 00 UTC, also provide data hourly, with steps from 01 to 24. The uncertainty is currently provided by ERA5 EDA fields, which are available every 3 hours for the surface fields.

Accumulations

The accumulations in the short forecasts of ERA5-Land (with hourly steps from 01 to 24) are treated the same as those in ERA-Interim or ERA-Interim/Land, i.e., they are accumulated from the beginning of the forecast to the end of the forecast step. For example, runoff at day=D, step=12 will provide runoff accumulated from day=D, time=0 to day=D, time=12. The maximum accumulation is over 24 hours, i.e., from day=D, time=0 to day=D+1,time=0 (step=24).

• HRES: accumulations are from 00 UTC to the hour ending at the forecast step
• For the CDS time, or validity time, of 00 UTC, the accumulations are over the 24 hours ending at 00 UTC i.e. the accumulation is during the previous day
• Synoptic monthly means (stream=mnth): accumulations have units of "variable_units per forecast_step hours"
  
• Monthly means of daily means (stream=moda): accumulations have units that include "per day", see section Monthly means

Monthly means

In addition to the sub-daily data, all ERA5-Land parameters are also available as monthly means. Monthly means are available in two forms:

• Synoptic monthly means, for each particular time and forecast step (stream=mnth) - in the CDS, referred to as "monthly averaged by hour of day".
• Monthly means of daily means, for the month as a whole (stream=moda) - in the CDS, referred to as "monthly averaged". These monthly means are created from the hourly data for the HRES.

Monthly means for:

• parameters labelled as analyses or instantaneous forecasts are created from data with a valid time in the month, between 00 and 23 UTC on each day of the month.
• accumulations are created from data with a forecast period falling within the month. Monthly means of daily means for accumulations are created from the last forecast step (24) of the forecasts for each day of the month.

The accumulations in monthly means of daily means (stream=moda) have units that include "per day". So for accumulations in this stream:

• The hydrological parameters are in units of "m of water equivalent per day" and so they should be multiplied by 1000 to convert to kgm^-2day^-1 or mmday^-1.
• The energy (turbulent and radiative) and momentum fluxes should be divided by 86400 seconds (24 hours) to convert to the commonly used units of Wm^-2 and Nm^-2, respectively.

The accumulations in synoptic monthly means (stream=mnth) have units that include "variable_units per forecast_step hours". So for accumulations in this stream: 

• The hydrological parameters are in units of "m of water equivalent per forecast_step hours" and so they should be multiplied by 1000 to convert to kgm^-2 per forecast_step hours or mm per forecast_step hours.
• The energy (turbulent and radiative) and momentum fluxes should be divided by 60 x 60 x fc_step to convert to the units of Wm^-2 and Nm^-2, respectively.
  

Data format

Surface fields in ERA5-Land are encoded either in GRIB1 or GRIB2 format. Tables 1 and 2 indicate the format for all parameters in ERA5-Land. Note that the retrieval of the data in NetCDF format is still possible via the CDS. 

The article "What are GRIB files" might be helpful.

Parameter listings

Tables 1 and 2 below describe the surface parameters available in ERA5-Land (levtype=sfc). Information on all ECMWF parameters is available from the ECMWF parameter database. To download auxiliary land invariant parameters, please use ERA5 (see table1 of ERA5 documentation)

Parameters described as "instantaneous" below, are valid at the specified time.

Note that in the tables below, "an" and "fc" is just a label used for convention to archive the data in MARS. 

Table 1: stream=oper/mnth/moda, levtype=sfc: surface parameters: instantaneous

Table 2: stream=oper/mnth/moda, levtype=sfc: surface parameters: accumulations

Accumulations are described in section ERA5-Land data documentation. The accumulations in monthly means (stream=moda/mnth) are described in section monthly means

How to use lake-related fields

Independently whether a model grid point is over a lake or not, the IFS computes lake variables all over the globe, at each grid-box. This is to ease output field aggregation at diverse model resolutions and to have a warm start of the model with shorter spin-up time if lake cover is upgraded, i.e.,  it is still a decent lake initial condition if lake location are updated or a new lake is added operationally. Lake depths (input parameter for our lake parametrization) are specified for each grid-box either with in-situ values or with a default 25 m value; over ocean we use ocean bathymetry. Worth to mention that the later default values will be changed soon (extra information in this HESS reference). The computed  lake variable values are not taken into account in the total grid-box flux calculations if lake is not present in the grid-box.

The lake fields provided in ERA5-Land can be used in combination with the lake location. The latter in the model is determined by lake cover field (parameter name CL, in fraction: 0 - grid-box has no lakes, 1 - grid-box is fully covered with lake/s). Lake depths are presented in the field DL (in meters).

The ECMWF model also contains an ice module, a snow module and a bottom sediments module. The present setup of the IFS is running with no bottom sediment and snow modules (snow accumulation over ice is not allowed and snow parameters are used only for albedo purposes). In the implementation in the IFS lake ice can be fractional within a grid-box with inland water (10 cm of ice means 100 % of a grid-box or tile is covered with ice; 0 cm of ice means 100 % of the grid-box is covered by water; in between a linear interpolation is applied) (Manrique-Sunen et al., 2013). At present, the water balance equation is not included for lakes and the lake depth and surface area are kept constant in time (IFS Documentation, 2017, chapter 8 and 11 ). Lake parametrization also requires the lake fraction CL, lake depth DL (preferably bathymetry), and lake initial conditions. DL is the most important external parameter that uses the lake parametrization.

Known issues

At the time of writing (May 2019) we are not aware of any issues with ERA5-Land

How to cite ERA5-Land

Please acknowledge the use of ERA5-Land as stated in the Copernicus C3S/CAMS License agreement:

• "5.1.2 Where the Licensee communicates or distributes Copernicus Products to the public, the Licensee shall inform the recipients of the source by using the following or any similar notice: 'Generated using Copernicus Climate Change Service Information [Year]'.

• 5.1.3 Where the Licensee makes or contributes to a publication or distribution containing adapted or modified Copernicus Products, the Licensee shall provide the following or any similar notice: 'Contains modified Copernicus Climate Change Service Information [Year]';

5.1.3 Any such publication or distribution covered by clauses 5.1.1 and 5.1.2 shall state that neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus Information or Data it contains."

You may also cite the ERA5-Land dataset as follows:

Dataset citable as: Copernicus Climate Change Service (C3S) (2019): C3S ERA5-Land reanalysis . Copernicus Climate Change Service, date of access. https://cds.climate.copernicus.eu/cdsapp#!/home

References

ERA5-Land news

Further ERA5-Land references and related information are available from the ECMWF e-Library.

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