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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 1981 1950 to 2-3 months before the present. The back-extension from 1950 started production in early 2020 with the release planned by Q3-2020. In 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).

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	name	units	Variable name in CDS	shortName	paramId	an	fc	GRIB1	GRIB2	Used as forcing field
1	Lake mix-layer temperature	K	lake_mix_layer_temperature	lmlt	228008	x		x
2	Lake mix-layer depth	m	lake_mix_layer_depth	lmld	228009	x		x
3	Lake bottom temperature	K	lake_bottom_temperature	lblt	228010	x		x
4	Lake total layer temperature	K	lake_total_layer_temperature	ltlt	228011	x		x
5	Lake shape factor	dimensionless	lake_shape_factor	lshf	228012	x		x
6	Lake ice temperature	K	lake_ice_temperature	lict	228013	x		x
7	Lake ice depth	m	lake_ice_depth	licd	228014	x		x
8	Snow cover	%	snow_cover	snowc	260038		x		x
9	Snow depth	m	snow_depth	sde	3066		x		x
10	Snow albedo	(0 - 1)	snow_albedo	asn	32	x		x
11	Snow density	kg m**-3	snow_density	rsn	33	x		x
12	Volumetric soil water layer 1¹	m3 m-3	volumetric_soil_water_layer_1	swvl1	39	x		x
13	Volumetric soil water layer 2¹	m3 m-3	volumetric_soil_water_layer_2	swvl2	40	x		x
14	Volumetric soil water layer 3¹	m3 m-3	volumetric_soil_water_layer_3	swvl3	41	x		x
15	Volumetric soil water layer 4¹	m3 m-3	volumetric_soil_water_layer_4	swvl4	42	x		x
16	Leaf area index, low vegetation²	m2 m-2	leaf_area_index_low_vegetation	lai_lv	66		x	x
17	Leaf area index, high vegetation²	m2 m-2	leaf_area_index_high_vegetation	lai_hv	67		x	x
18	Surface pressure	Pa	surface_pressure	sp	134		x	x		x
19	Soil temperature level 1¹	K	soil_temperature_level_1	stl1	139	x		x
20	Snow depth water equivalent	m of water equivalent	snow_depth_water_equivalent	sd	141	x		x
21	10 metre U wind component	m s**-1	10m_u_component_of_wind	u10	165		x	x		x
22	10 metre V wind component	m s**-1	10m_v_component_of_wind	v10	166		x	x		x
23	2 metre temperature	K	2m_temperature	2t	167		x	x
24	2 metre dewpoint temperature	K	2m_dewpoint_temperature	2d	168		x	x
25	Soil temperature level 2¹	K	soil_temperature_level_2	stl2	170	x		x
26	Soil temperature level 3¹	K	soil_temperature_level_3	stl3	183	x		x
27	Skin reservoir content	m of water equivalent	skin_reservoir_content	src	198	x
28	Skin temperature	K	skin_temperature	skt	235	x		x
29	Soil temperature level 4¹	K	soil_temperature_level_4	stl4	236	x		x
30	Temperature of snow layer	K	temperature_of_snow_layer	tsn	238	x		x
31	Forecast albedo	(0 - 1)	forecast_albedo	fal	243		x	x

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	name	units	Variable name in CDS	shortName	paramId	fc	GRIB1	GRIB2	Used as forcing field
1	Surface runoff	m	surface_runoff	sro	8	x	x
2	Sub-surface runoff	m	sub_surface_runoff	ssro	9	x	x
3	Snowmelt	m of water equivalent	snowmelt	smlt	45	x	x
4	Snowfall	m of water equivalent	snowfall	sf	144	x	x		x
5	Surface sensible heat flux	J m**-2	surface_sensible_heat_flux	sshf	146	x	x
6	Surface latent heat flux	J m**-2	surface_latent_heat_flux	slhf	147	x	x
7	Surface solar radiation downwards	J m**-2	surface_solar_radiation_downwards	ssrd	169	x	x		x
8	Surface thermal radiation downwards	J m**-2	surface_thermal_radiation_downwards	strd	175	x	x		x
9	Surface net solar radiation	J m**-2	surface_net_solar_radiation	ssr	176	x	x		x
10	Surface net thermal radiation	J m**-2	surface_net_thermal_radiation	str	177	x	x		x
11	Total Evaporation	m of water equivalent	total_evaporation	e	182	x	x
12	Runoff	m	runoff	ro	205	x	x
13	Total precipitation	m	total_precipitation	tp	228	x	x		x
14	Evaporation from the top of canopy	m of water equivalent	evaporation_from_the_top_of_canopy	evatc	228100	x		x
15	Evaporation from bare soil	m of water equivalent	evaporation_from_bare_soil	evabs	228101	x		x
16	Evaporation from open water surfaces excluding oceans	m of water equivalent	evaporation_from_open_water_surfaces_excluding_oceans	evaow	228102	x		x
17	Evaporation from vegetation transpiration	m of water equivalent	evaporation_from_vegetation_transpiration	evavt	228103	x		x
18	Potential evaporation	m	potential_evaporation	pev	228251	x	x

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title	Actual and potential evapotranspiration

Actual evapotranspiration in the ERA5-Land datasets is called "Total Evaporation" (param ID 182) and is the sum of the following four evaporation components:

For the ERA5-Land datasets, actual evapotranspirationand it's four components can be downloaded from the C3S Climate Data Store (CDS) under the category heading "Evaporation and Runoff".

For details about the computation of actual evapotranspiration, please see Chapter 8 of Part IV : Physical processes, of the IFS documentation:

ERA5-Land IFS cycle 45r1

The potential evapotranspiration in the ERA5-Land CDS dataset is given by the parameter potential evaporation (pev).

Pev data can be downloaded from the CDS under the category heading "Evaporation and Runoff", in the "Download data" tab for the ERA5-Land datasets.

Note
The definitions of potential and reference evapotranspiration may vary according to the scientific application and can have the same definition in some cases. Users should therefore ensure that the definition of this parameter is suitable for their application.

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title	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

Expand

title	Uncertainty fields

As it was done for ERA5, the original plan for ERA5-Land was to provide an estimate of the uncertainty fields based on a dedicated 10-member ensemble run. The latter generated an ensemble of forcing fields that should, in principle, reproduce the space of uncertainty for the land surface fields. The first experiments demonstrated that the spread of the ensemble was clearly under dispersive, i.e. the uncertainty was unrealistically low. A reason for this is the low spread shown by the ensemble of ERA5 forcing fields.

As a result of these experiments we took the decision of not providing the uncertainty fields of ERA5-Land. The opposite would have assigned, for instance, unrealistically high confidence to ERA5-land fields in a data assimilation experiment.

Our recommendation is, for the time being, to use the uncertainty estimate of the corresponding ERA5 field, which should provide a second order approximation to the estimate of the real uncertainty. Future experiments will also perturbe, among other, key land surface model parameters, therefore providing a more realistic spread of the ERA5-Land ensemble surface fields.

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Three components of the total evapotranspiration have values swapped as follows:

- variable "Evaporation from bare soil" (mars parameter code 228101 (evabs)) has the values corresponding to the "Evaporation from vegetation transpiration" (mars parameter 228103 (evavt)),
- variable "Evaporation from open water surfaces excluding oceans (mars parameter code 228102 (evaow)) has the values corresponding to the "Evaporation from bare soil" (mars parameter code 228101 (evabs)),
- variable "Evaporation from vegetation transpiration" (mars parameter code 228103 (evavt)) has the values corresponding to the "Evaporation from open water surfaces excluding oceans" (mars parameter code 228102 (evaow)).

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title	Low values of snow cover and snow depth on the eastern side of the Antarctic ice sheet

Note

Please note that based on ERA5-Land atmospheric forcing, other independent (offline) methods such us "Priesley-Taylor¹ (1972) , Schmidt² (1915) or de Bruin³ (2000)" can also be used to estimate Potential evapotranspiration.

¹PRIESTLEY, C. H. B., & TAYLOR, R. J. (1972). On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters, Monthly Weather Review, 100(2), 81-92. Retrieved Aug 27, 2021, from https://journals.ametsoc.org/view/journals/mwre/100/2/1520-0493_1972_100_0081_otaosh_2_3_co_2.xml

²Schmidt, W., 1915: Strahlung und Verdunstung an freien Wasserflächen; ein Beitrag zum Wärmehaushalt des Weltmeers und zum Wasserhaushalt der Erde (Radiation and evaporation over open water surfaces; a contribution to the heat budget of the world ocean and to the water budget of the earth). Ann. Hydro. Maritimen Meteor., 43, 111–124, 169–178.

³de Bruin, H. A. R., , and Stricker J. N. M. , 2000: Evaporation of grass under non-restricted soil moisture conditions. Hydrol. Sci. J., 45, 391–406, doi:10.1080/02626660009492337.

Expand

title	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

Expand

title	Uncertainty fields

As it was done for ERA5, the original plan for ERA5-Land was to provide an estimate of the uncertainty fields based on a dedicated 10-member ensemble run. The latter generated an ensemble of forcing fields that should, in principle, reproduce the space of uncertainty for the land surface fields. The first experiments demonstrated that the spread of the ensemble was clearly under dispersive, i.e. the uncertainty was unrealistically low. A reason for this is the low spread shown by the ensemble of ERA5 forcing fields.

As a result of these experiments we took the decision of not providing the uncertainty fields of ERA5-Land. The opposite would have assigned, for instance, unrealistically high confidence to ERA5-land fields in a data assimilation experiment.

Our recommendation is, for the time being, to use the uncertainty estimate of the corresponding ERA5 field, which should provide a second order approximation to the estimate of the real uncertainty. Future experiments will also perturbe, among other, key land surface model parameters, therefore providing a more realistic spread of the ERA5-Land ensemble surface fields.

Three components of the total evapotranspiration have values swapped as follows:
- variable "Evaporation from bare soil" (mars parameter code 228101 (evabs)) has the values corresponding to the "Evaporation from vegetation transpiration" (mars parameter 228103 (evavt)),
- variable "Evaporation from open water surfaces excluding oceans (mars parameter code 228102 (evaow)) has the values corresponding to the "Evaporation from bare soil" (mars parameter code 228101 (evabs)),
- variable "Evaporation from vegetation transpiration" (mars parameter code 228103 (evavt)) has the values corresponding to the "Evaporation from open water surfaces excluding oceans" (mars parameter code 228102 (evaow)).

Expand

title	Low values of snow cover and snow depth on the eastern side of the Antarctic ice sheet

Low values of snow cover and snow depth were found on the eastern side of the Antarctic ice sheet, as shown in Fig. 1. The issue is due to the application of an old glacier mask to the Antarctica, which excludes the patch shown in the figure as glacier. Inaccuracies in the glacier mask are due to errors in satellite measurements datasets. While, due to the lower horizontal resolution, in ERA5 this ice sheet part is a sea point, in ERA5-Land the area is categorised as land without an initial ice mass. Since the initialization doesn't consider a glacier there (estimated at a constant 10 m of snow water equivalent), the low amount of precipitation along with potential excess of sublimation makes them to obtain unrealistic low numbers there.

Image Added

Fig 1: ERA-Land Snow depth (m of water equivalent) on 01-01-2015 eastern side of the Antarctic ice sheet.

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title	Limited impact from sub-optimal tropical cyclones in the forcing from the ERA5 preliminary dataset for 1950-1978.

From 1950-1978 ERA5-Land was forced by the preliminary ERA5 back extension which has a sub-optimal representation for a number of tropical cyclones.

The over-estimation of a number of tropical cyclones for this period affects some products over the oceans in the vicinity of tropical cyclone tracks. Over land much smaller impact is expected, and therefore, the effect on the ERA5-Land product from 1950-1978 is more limited.

This is supported by the figure below that plots, for each location, the minimum pressure from the ERA5 forcing (top panels) and the maximum daily accumulated total precipitation for ERA5-Land (lower panels) for the (preliminary) back extension (left panels) and for the period from the late 1970s to 2010 inclusive (right panels). Note that these show the most extreme situations, i.e., the absolute extremes in the about 30-year periods that were considered in each plot. Less extreme statistics, like 99, 95 (etc.) percentiles or mean distributions will show a much smaller impact of tropical cyclones.

From these panels it is seen that for the forcing from ERA5 (top panels), in general, local minimum pressure is similar between 1950-1978 and 1979-2010. There are of course sampling differences between the two, each about 30-year, periods. Large differences that are likely related to anomalously strong tropical cyclones are very localized, such as for some areas over North Australia, East Madagascar, Philippines and Northeast China. Note again that these affect a few cases only in the 29-year dataset.

The effect on the ERA5-Land precipitation is shown in the lower panels. Even for these extremes it is difficult to pin-point locations that could be affected by anomalous tropical cyclones.

Image Added	Image Added
Image Added	Image Added

Caption: locally minimum of 6-hourly pressure for ERA5 forcing data (top panels) and maximum daily total precipitation (lower panels) over the indicated period of time for the back extension (left panels) and for later periods (right panels). Numbers represent the averages for the locally extreme values over the indicated areas

Low values of snow cover and snow depth were found on the eastern side of the Antarctic ice sheet, as shown in Fig. 1. The issue is due to the application of an old glacier mask to the Antarctica, which excludes the patch shown in the figure as glacier. Inaccuracies in the glacier mask are due to errors in satellite measurements datasets. While, due to the lower horizontal resolution, in ERA5 this ice sheet part is a sea point, in ERA5-Land the area is categorised as land without an initial ice mass. Since the initialization doesn't consider a glacier there (estimated at a constant 10 m of snow water equivalent), the low amount of precipitation along with potential excess of sublimation makes them to obtain unrealistic low numbers there.

Image Removed

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How to cite ERA5-Land

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

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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."

(2) cite the ERA5-Land dataset (as part of the bibliography) as follows:

For "ERA5-Land

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hourly data from 1950 to present" downloaded from the Climate Data Store:

Muñoz Sabater, J., (2019): ERA5-Land hourly data from 1981 to present

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. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Accessed on < DD-MMM-YYYY >), 10.24381/cds.e2161bac

Muñoz Sabater, J., (

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2021): ERA5-Land hourly data from

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1950 to

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1980. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Accessed on < DD-MMM-YYYY >), 10.24381/cds.e2161bac

For "ERA5-Land monthly averaged data from 1981 1950 to present" downloaded from the Climate Data Store:

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

J. Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: A state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci Sci. Data Discuss. [preprint], ,13, 4349–4383, 2021. https://doi.org/10.5194/essd-2021-82, in review, 13-4349-2021.

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This document has been produced in the context of the Copernicus Climate Change Service (C3S).

The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation agreement signed on 11/11/2014). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.

The users thereof use the information at their sole risk and liability. For the avoidance of all doubt, the European Commission and the European Centre for Medium-Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view.

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How to cite ERA5-Land

This document has been produced in the context of the Copernicus Climate Change Service (C3S).

The users thereof use the information at their sole risk and liability. For the avoidance of all doubt, the European Commission and the European Centre for Medium-Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view.