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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°).

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Table 1: surface parameters: invariants (in time)

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

surface_pressure

skin_reservoir_content

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Table 3: stream=oper/mnth/moda, levtype=sfc: surface parameters: accumulations

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

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1. 
   

   Expand
   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: Evaporation from bare soil Evaporation from open water surfaces excluding oceans Evaporation from the top of canopy Evaporation from vegetation transpiration 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 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. 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. to give more flexibilty to users,  PEV in ERA5 and ERA5Land are not computed in the same way: ERA5: the definition of PEV in ERA5 is computed for agricultural land as if it is well watered (no soil moisture stress)  and assuming that the atmosphere is not affected by this artificial surface condition.  ERA5Land: the definition of PEV in ERA5Land is computed as an open water evaporation (Pan evaporation) and assuming that the atmosphere is not affected by this artificial surface condition. 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.

   
   

2. 
   

   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
   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.

   
   

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1. 
   

   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.

   
   

2. 
   

   Expand
   title Swapped value of the components of the total evapotranspiration
   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)).

   
   

3. 
   

   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.

    

   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.

   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.   Fig 1: ERA-Land Snow depth (m of water equivalent) on 01-01-2015 eastern side of the Antarctic ice sheet.
   Expand
   title Limited impact from sub-optimal tropical cyclones in the forcing from the ERA5 preliminary dataset for 1950-1978.
   Image Removed	Image Removed
   Image Removed	Image Removed

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2. 
   

   Expand
   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.

   
   

3. 
   

   Expand
   title Definition of Potential Evaporation (PEV) modified
   Note that on 18-11-2021 we modified the definition of Potential Evaporation (PEV) provided in the CDS catalogue entry for both, the hourly and the monthly fields. The reason is that until this date the definition of PEV was similar to that of the same field provided by ERA5, whereas in reality they are computed differently:    PEV in ERA5 is computed for agricultural land as if it is well watered (no soil moisture stress)  and assuming that the atmosphere is not affected by this artificial surface condition.   PEV in ERA5-Land is computed as an open water evaporation (Pan evaporation) and assuming that the atmosphere is not affected by this artificial surface condition.

   
   

How to cite the ERA5-Land dataset

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

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Muñoz Sabater, J., (2019): ERA5-Land hourly data from 1981 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Accessed on < DD-MMM-YYYY >), 10.24381/cds.e2161bace2161bac

Muñoz Sabater, J., (2021): ERA5-Land hourly data from 1950 to 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 1950 to present" downloaded from the Climate Data Store:

Muñoz Sabater, J., (

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2019): ERA5-Land

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monthly averaged data from

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1981 to

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

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68d2bb3

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

Muñoz Sabater, J., (20192021): ERA5-Land monthly averaged data from 1981 1950 to present1980. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Accessed on < DD-MMM-YYYY >), 10.24381/cds.68d2bb3

References

ERA5-Land news

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

Reference articles

J. Muñoz-Sabater, 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. Data,13, 4349–4383, 2021. https://doi.org/10.5194/essd-13-4349-2021.

ERA5-Land news

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

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