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Introduction

Here we document the ERA5 dataset, which, eventually, will cover the period from January 1950. ERA5 data released so far covers the period from 1979 and continues to be extended forward in near real time.

ERA5 was produced using 4D-Var data assimilation in CY41R2 of ECMWF’s Integrated Forecast System (IFS), with 137 hybrid sigma/pressure (model) levels in the vertical, with the top level at 0.01 hPa. Atmospheric data are available on these levels and they are also interpolated to 37 pressure, 16 potential temperature and 1 potential vorticity level(s). "Surface or single level" data are also available, containing 2D parameters such as precipitation, 2m temperature, top of atmosphere radiation and vertical integrals over the entire atmosphere. The IFS is coupled to a soil model, the parameters of which are also designated as surface parameters, and an ocean wave model.

The ERA5 dataset contains one (31 km) high resolution realisation (HRES) and a reduced resolution ten member ensemble (EDA). Generally, the data are available at a sub-daily and monthly frequency and consist of analyses and short (18 hour) forecasts, initialised twice daily from analyses at 06 and 18 UTC. Most analysed parameters are also available from the forecasts. There are a number of forecast parameters, e.g. mean rates and accumulations, that are not available from the analyses.

How to download ERA5

The data are archived in the ECMWF data archive (MARS) and a pertinent sub-set of the data, interpolated to a regular latitude/longitude grid, has been copied to the Climate Data Store (CDS) disks.

Documentation is available on how to download ERA5 data. (Member State users can access the data directly from MARS, in the usual manner.) Data can be downloaded either from the relevant CDS download page or using the CDS API. The latter is suitable for larger data volumes and for accessing the ERA5 data in MARS.

Data format

Model level fields (see below) are in GRIB2 format. All other fields are in GRIB1, unless otherwise indicated.

In the CDS, there is the option of retrieving the data in netCDF format.

Data update frequency

Initial release data, i.e. data no more than three months behind real time, is called ERA5T.  In the event that serious flaws are detected in ERA5T, this data could be different to the final ERA5 data. In practice, though, this will be very unlikely to occur. Based on experience with the production of ERA5 so far (and ERA-Interim in the past), our expectation is that such an event would not occur more than once every few years, if at all. In the unlikely event that such a correction is required, users will be notified as soon as possible.

For the CDS, daily updates are available 5 days behind real time and monthly mean updates are available 5 days after the end of the month.

For MARS ERA5 data, monthly updates are available about two months after the month in question. In the future, ERA5T data will also be available in MARS.

For GRIB data, ERA5T can be identified by the key expver=0005 in the GRIB header. ERA5 is identified by the key expver=0001.

For netCDF data requests which return just ERA5 or just ERA5T data, there is no means of differentiating between ERA5 and ERA5T data in the resulting netCDF files.

For netCDF data requests which return a mixture of ERA5 and ERA5T data, the origin of the variables (1 or 5) will be identifiable in the resulting netCDF files. See the link for more details.

The IFS and data assimilation

The model documentation for CY41R2 is at https://www.ecmwf.int/en/publications/search/?solrsort=sort_label%20asc&secondary_title=%22IFS%20Documentation%20CY41R2%22

The 4D-Var data assimilation uses 12 hour windows from 09 UTC to 21 UTC and 21 UTC to 09 UTC (the following day).

The model time step is 12 minutes for the HRES and 20 minutes for the EDA, though occasionally these numbers are adjusted to cope with instabilities.

Data organisation

The data can be accessed from MARS using the keywords class=ea and expver=0001 (expver=0005 for ERA5T). Subdivisions of the data are labelled using stream, type and levtype.

Stream:

  • oper: HRES sub-daily
  • wave: HRES waves sub-daily
  • mnth: HRES synoptic monthly means
  • moda: HRES monthly means of daily means
  • wamo: HRES waves synoptic monthly means
  • wamd: HRES waves monthly means of daily means
  • enda: EDA sub-daily
  • ewda: EDA waves sub-daily
  • edmm: EDA synoptic monthly means
  • edmo: EDA monthly means of daily means
  • ewmm: EDA waves synoptic monthly means
  • ewmo: EDA waves monthly means of daily means

Type:

  • an: analyses
  • fc: forecasts
  • em: ensemble mean
  • es: ensemble standard deviation

Levtype:

  • sfc: surface or single level
  • pl: pressure levels
  • pt: potential temperature levels
  • pv: potential vorticity level
  • ml: model levels


In MARS: the date and time of the data is specified with three MARS keywords, date, time and step. For analyses, step=0 hours so that date and time specify the analysis time. For forecasts, date and time specify the forecast start time and step specifies the number of hours since that start time. The combination of date, time and forecast step defines the validity time. For analyses, the validity time is equal to the analysis time.

In the CDS: analyses are provided rather than forecasts, unless the parameter is only available from the forecasts. The date and time of the data is specified using the validity date/time, so step does not need to be specified. For forecasts, steps between 1 and 12 hours have been used to provide data for all the validity times in 24 hours, see Table 0 below.


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

CDS

date  time

MARS

date      time  step


CDS

date  time

MARS

date   time  step

date  00

date-1  18        06


date  12

date   06      06

date  01

date-1  18        07


date  13

date   06      07

date  02

date-1  18        08


date  14

date   06      08

date  03

date-1  18        09


date  15

date   06      09

date  04

date-1  18        10


date  16

date   06      10

date  05

date-1  18        11


date  17

date   06      11

date  06

date-1  18        12


date  18

date   06      12

date  07

date      06        01


date  19

date   18      01

date  08

date      06        02


date  20

date   18      02

date  09

date      06        03


date  21

date   18      03

date  10

date      06        04


date  22

date   18      04

date  11

date      06        05


date  23

date   18      05


Spatial grid

The ERA5 HRES atmospheric data has a resolution of 31km, 0.28125 degrees, and the EDA has a resolution of 63km, 0.5625 degrees. (Depending on the parameter, the data are archived either as spectral coefficients with a triangular truncation of T639 (HRES) and T319 (EDA) or on a reduced Gaussian grid with a resolution of N320 (HRES) and N160 (EDA). These grids are so called "linear grids", sometimes referred to as TL639 (HRES) and TL319 (EDA).)

The wave data are produced and archived on a different grid to that of the atmospheric model, namely a reduced latitude/longitude grid with a resolution of 0.36 degrees (HRES) and 1.0 degrees (EDA).

ERA5 data available from the CDS disks has been pre-interpolated to a regular latitude/longitude grid appropriate for that data.

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

Temporal frequency

For sub-daily data for the HRES (stream=oper/wave) the analyses (type=an) are available hourly. The short forecasts, run from 06 and 18 UTC, have hourly steps from 0 to 18 hours. For the EDA, the sub-daily non-wave data (stream=enda) are available every 3 hours but the sub-daily wave data (stream=ewda) are available hourly.

Wave spectra

The ERA5 wave model uses wave spectra with 24 directions and 30 frequencies (see "2D wave spectra (single)", Table 7),

 Decoding 2D wave spectra

Download from ERA5

ERA5 data is available through the Climate Data Store (CDS). However some ERA5 datasets do not appear in CDS but are accessible through CDS API (for example, ERA5 wave spectra data, ERA5 model level data and ERA5 monthly means archived at ECMWF's MARS archive). The ERA5 Wave data is currently archived in the ECMWF MARS tape library. To retrieve this data, you will need to use MARS Keywords in your CDS API request. Details are available from How to download ERA5 (Section 3 - Step C: Download ERA5 data NOT listed in CDS through CDS API).

Decoding 2D wave spectra in GRIB

To decode wave spectra in GRIB format we recommend ecCodes. Wave spectra are encoded in a specific way that other tools might not decode correctly.

In GRIB, the parameter is called 2d wave spectra (single) because in GRIB, the data are stored as a single global field per each spectral bin (a given frequency and direction), but in NetCDF, the fields are nicely recombined to produce a 2d matrix representing the discretized spectra at each grid point.

The wave spectra are encoded in GRIB using a local table specific to ECMWF. Because of this, the conversion of the meta data containing the information about the frequencies and the directions are not properly converted from GRIB to NetCDF format. So rather than having the actual values of the frequencies and directions, values show index numbers (1,1) : first frequency, first direction, (1,2) first frequency, second direction, etc ....

For ERA, because there are a total of 24 directions, the direction increment is 15 degrees with the first direction given by half the increment, namely 7.5 degree, where direction 0. means going towards the north and 90 towards the east (Oceanographic convention), or more precisely, this should be expressed in gradient since the spectra are in m^2 /(Hz radian)
The first frequency is 0.03453 Hz and the following ones are : f(n) = f(n-1)*1.1, n=2,30

Also note that it is NOT the spectral density that is encoded but rather log10 of it, so to recover the spectral density, expressed in m^2 /(radian Hz), one has to take the power 10 (10^) of the NON missing decoded values. Missing data are for all land points, but also, as part of the GRIB compression, all small values below a certain threshold have been discarded and so those missing spectral values are essentially 0. m^2 /(gradient Hz).

Decoding 2D wave spectra in NetCDF

The NetCDF wave spectra file will have the dimensions longitude, latitude, direction, frequency and time.

However, the direction and frequency bins are simply given as 1 to 24 and 1 to 30, respectively.

The direction bins start at 7.5 degree and increase by 15 degrees until 352.5, with 90 degree being towards the east (Oceanographic convention).

The frequency bins are non-linearly spaced. The first bin is 0.03453 Hz and the following bins are: f(n) = f(n-1)*1.1; n=2,30. The data provided is the log10 of spectra density. To obtain the spectral density one has to take to the power 10 (10 ** data). This will give the units 2D wave spectra as m**2 s radian**-1 . Very small values are discarded and set as missing values. These are essentially 0 m**2 s radian**-1.

This recoding can be done with the Python xarray package, for example:

import xarray as xr
import numpy as np
da = xr.open_dataarray('2d_spectra_201601.nc')
da = da.assign_coords(direction=np.arange(7.5, 352.5 + 15, 15))
da = da.assign_coords(frequency=np.full(30, 0.03453) * (1.1 ** np.arange(0, 30)))
da = 10 ** da
da = da.fillna(0)
da.to_netcdf(path='2d_spectra_201601_recoded.nc')

Units of 2D wave spectra

Once decoded, the units of 2D wave spectra are m2 s radian-1

Mean rates and accumulations

The accumulations in the short forecasts (from 06 and 18 UTC) of ERA5 are treated differently compared with those in ERA-Interim and operational data (where they are from the beginning of the forecast to the forecast step). In the short forecasts of ERA5 the accumulations are since the previous post processing (archiving), so for:

  • HRES: accumulations are over the hour ending at the forecast step
  • EDA: accumulations are over the 3 hours ending at the forecast step
  • Monthly means of daily means (stream=moda/edmo): accumulations have been scaled to have units that include "per day", see section Monthly means

Mean rate parameters in ERA5 are similar to accumulations except that the accumulations have been divided by the length of the processing period in seconds to produce temporally averaged rates, so the units include "per second". For "surface or single level" parameters, the mean rates (Table 4) provide similar information to the accumulations (Table 3), but with the different units.

Note that:

  • For the CDS time, or validity time, of 00 UTC, the mean rates and accumulations are over the hour (3 hours for the EDA) ending at 00 UTC i.e. the mean or accumulation is during the previous day.
  • Mean rates and accumulations are not available from the analyses.
  • Mean rates and accumulations at step=0 have values of zero because the length of the processing period is zero.

Minimum/maximum since the previous post processing

The short forecasts of ERA5 contain some surface and single level parameters that are the minimum or maximum value since the previous post processing (archiving), see Table 5 below. So, for:

  • HRES: the minimum or maximum values are in the hour ending at the forecast step
  • EDA: the minimum or maximum values are in the 3 hours ending at the forecast step

Monthly means

In addition to the sub-daily data, most parameters are also available as monthly means. For the surface and single level parameters, there are some exceptions which are listed in Table 8.

Monthly means are available in two forms:

  • Synoptic monthly means, for each particular time and forecast step (stream=mnth/wamo/edmm/ewmm) - 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/wamd/edmo/ewmo) - in the CDS, referred to as "monthly averaged". These monthly means are created from the hourly data for the reanalysis (HRES) and 3 hourly data for the ensemble members (EDA).

Monthly means for:

  • forecast parameters are created using the first 12 hours of the twice daily short forecasts (beginning at 06 and 18 UTC).
  • analysis and instantaneous forecast parameters are created from data with a valid time in the month, between 00 and 23 UTC, which excludes the time 00 UTC on the first day of the following month.
  • accumulation and mean rate forecast parameters are created from data with a forecast period falling within the month. Therefore, monthly means of daily means for accumulations and mean rates are created from contiguous data with forecast periods spanning from 00 UTC on the first day of the month to 00 UTC on the first day of the following month.

The accumulations in monthly means of daily means (stream=moda/edmo) have been scaled to have units that include "per day", so for accumulations in these streams:

  • The hydrological parameters are in units of "m of water 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.

Ensemble means and standard deviations

For the EDA sub-daily data (stream=enda/ewda), compared with HRES sub-daily data (stream=oper/wave), there are also ensemble means and standard deviations (type=em/es).

Ensemble standard deviation is often referred to as ensemble spread and is calculated as the standard deviation of the 10-members in the ensemble (i.e., including the control). It is not the sample stdv, so we divide by 10 rather than 9 (N-1). 

Ensemble means and standard deviations contain analysed parameters when step=0, otherwise they contain forecast parameters. However, only surface and pressure level data (levtype=sfc/pl) contain forecast steps beyond 3 hours. There are no monthly means for ensemble means and standard deviations.

Level listings

Pressure levels: 1000/975/950/925/900/875/850/825/800/775/750/700/650/600/550/500/450/400/350/300/250/225/200/175/150/125/100/70/50/30/20/10/7/5/3/2/1

Potential temperature levels: 265/275/285/300/315/320/330/350/370/395/430/475/530/600/700/850

Potential vorticity level: 2000

Model levels: 1/to/137, which are described at https://www.ecmwf.int/en/forecasts/documentation-and-support/137-model-levels.

Parameter listings

Tables 1-6 below describe the surface and single level parameters (levtype=sfc), Table 7 describes wave parameters, Table 8 describes the monthly mean exceptions for surface and single level and wave parameters and Tables 9-13 describe upper air parameters on various levtypes.

Information on all ECMWF parameters (e.g. columns shortName and paramId) is available from the ECMWF parameter database.

Note: If a parameter name listed in the tables below does not have a Variable name in CDS, this means that this particular parameter is only available from the ECMWF MARS tape archive using CDS-API (see Data Organisation section above).

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


Table 1: stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc: surface and single level parameters: invariants

count

name

units

Variable name in CDS

shortName

paramId

an

fc

1

Lake cover

(0 - 1)

lake_cover

cl

26

x

x

2

Lake depth

m

lake_depth

dl

228007

x

x

3

Low vegetation cover

(0 - 1)

low_vegetation_cover

cvl

27

x


4

High vegetation cover

(0 - 1)

high_vegetation_cover

cvh

28

x


5

Type of low vegetation

~

type_of_low_vegetation

tvl

29

x


6

Type of high vegetation

~

type_of_high_vegetation

tvh

30

x


7

Soil type

~

soil_type

slt

43

x


8

Standard deviation of filtered subgrid orography

m

standard_deviation_of_filtered_subgrid_orography

sdfor

74

x


9

Geopotential

m**2 s**-2

geopotential

z

129

x

x

10

Standard deviation of orography

~

standard_deviation_of_orography

sdor

160

x


11

Anisotropy of sub-gridscale orography

~

anisotropy_of_sub_gridscale_orography

isor

161

x


12

Angle of sub-gridscale orography

radians

angle_of_sub_gridscale_orography

anor

162

x


13

Slope of sub-gridscale orography

~

slope_of_sub_gridscale_orography

slor

163

x


14

Land-sea mask

(0 - 1)

land_sea_mask

lsm

172

x

x


Table 2: stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc: surface and single level parameters: instantaneous

count

name

units

Variable name in CDS

shortName

paramId

an

fc

1

Convective inhibition

J kg**-1

convective_inhibition

cin

228001


x

2

Friction velocity

m s**-1

friction_velocity

zust

228003


x

3

Lake mix-layer temperature

K

lake_mix_layer_temperature

lmlt

228008

x

x

4

Lake mix-layer depth

m

lake_mix_layer_depth

lmld

228009

x

x

5

Lake bottom temperature

K

lake_bottom_temperature

lblt

228010

x

x

6

Lake total layer temperature

K

lake_total_layer_temperature

ltlt

228011

x

x

7

Lake shape factor

dimensionless

lake_shape_factor

lshf

228012

x

x

8

Lake ice temperature

K

lake_ice_temperature

lict

228013

x

x

9

Lake ice depth

m

lake_ice_depth

licd

228014

x

x

10

UV visible albedo for direct radiation

(0 - 1)

uv_visible_albedo_for_direct_radiation

aluvp

15

x

x

11

Minimum vertical gradient of refractivity inside trapping layer

m**-1

minimum_vertical_gradient_of_refractivity_inside_trapping_layer

dndzn

228015


x

12

UV visible albedo for diffuse radiation

(0 - 1)

uv_visible_albedo_for_diffuse_radiation

aluvd

16

x

x

13

Mean vertical gradient of refractivity inside trapping layer

m**-1

mean_vertical_gradient_of_refractivity_inside_trapping_layer

dndza

228016


x

14

Near IR albedo for direct radiation

(0 - 1)

near_ir_albedo_for_direct_radiation

alnip

17

x

x

15

Duct base height

m

duct_base_height

dctb

228017


x

16

Near IR albedo for diffuse radiation

(0 - 1)

near_ir_albedo_for_diffuse_radiation

alnid

18

x

x

17

Trapping layer base height

m

trapping_layer_base_height

tplb

228018


x

18

Trapping layer top height

m

trapping_layer_top_height

tplt

228019


x

19

Cloud base height

m

cloud_base_height

cbh

228023


x

20

Zero degree level

m


deg0l

228024


x

21

Instantaneous 10 metre wind gust

m s**-1

instantaneous_10m_wind_gust

i10fg

228029


x

22

Sea ice area fraction

(0 - 1)

sea_ice_cover

ci

31

x

x

23

Snow albedo

(0 - 1)

snow_albedo

asn

32

x

x

24

Snow density

kg m**-3

snow_density

rsn

33

x

x

25

Sea surface temperature

K

sea_surface_temperature

sst

34

x

x

26

Ice temperature layer 1

K

ice_temperature_layer_1

istl1

35

x

x

27

Ice temperature layer 2

K

ice_temperature_layer_2

istl2

36

x

x

28

Ice temperature layer 3

K

ice_temperature_layer_3

istl3

37

x

x

29

Ice temperature layer 4

K

ice_temperature_layer_4

istl4

38

x

x

30

Volumetric soil water layer 11

m**3 m**-3

volumetric_soil_water_layer_1

swvl1

39

x

x

31

Volumetric soil water layer 21

m**3 m**-3

volumetric_soil_water_layer_2

swvl2

40

x

x

32

Volumetric soil water layer 31

m**3 m**-3

volumetric_soil_water_layer_3

swvl3

41

x

x

33

Volumetric soil water layer 41

m**3 m**-3

volumetric_soil_water_layer_4

swvl4

42

x

x

34

Convective available potential energy

J kg**-1

convective_available_potential_energy

cape

59

x

x

35

Leaf area index, low vegetation

m**2 m**-2

leaf_area_index_low_vegetation

lai_lv

66

x

x

36

Leaf area index, high vegetation

m**2 m**-2

leaf_area_index_high_vegetation

lai_hv

67

x

x

37

Neutral wind at 10 m u-component

m s**-1

10m_u_component_of_neutral_wind

u10n

228131

x

x

38

Neutral wind at 10 m v-component

m s**-1

10m_v_component_of_neutral_wind

v10n

228132

x

x

39

Surface pressure

Pa

surface_pressure

sp

134

x

x

40

Soil temperature level 11

K

soil_temperature_level_1

stl1

139

x

x

41

Snow depth

m of water equivalent

snow_depth

sd

141

x

x

42

Charnock

~

charnock

chnk

148

x

x

43

Mean sea level pressure

Pa

mean_sea_level_pressure

msl

151

x

x

44

Boundary layer height

m

boundary_layer_height

blh

159

x

x

45

Total cloud cover

(0 - 1)

total_cloud_cover

tcc

164

x

x

46

10 metre U wind component

m s**-1

10m_u_component_of_wind

10u

165

x

x

47

10 metre V wind component

m s**-1

10m_v_component_of_wind

10v

166

x

x

48

2 metre temperature

K

2m_temperature

2t

167

x

x

49

2 metre dewpoint temperature

K

2m_dewpoint_temperature

2d

168

x

x

50

Soil temperature level 21

K

soil_temperature_level_2

stl2

170

x

x

51

Soil temperature level 31

K

soil_temperature_level_3

stl3

183

x

x

52

Low cloud cover

(0 - 1)

low_cloud_cover

lcc

186

x

x

53

Medium cloud cover

(0 - 1)

medium_cloud_cover

mcc

187

x

x

54

High cloud cover

(0 - 1)

high_cloud_cover

hcc

188

x

x

55

Skin reservoir content

m of water equivalent

skin_reservoir_content

src

198

x

x

56

Instantaneous large-scale surface precipitation fraction

(0 - 1)

instantaneous_large_scale_surface_precipitation_fraction

ilspf

228217


x

57

Convective rain rate

kg m**-2 s**-1

convective_rain_rate

crr

228218


x

58

Large scale rain rate

kg m**-2 s**-1

large_scale_rain_rate

lsrr

228219


x

59

Convective snowfall rate water equivalent

kg m**-2 s**-1

convective_snowfall_rate_water_equivalent

csfr

228220


x

60

Large scale snowfall rate water equivalent

kg m**-2 s**-1

large_scale_snowfall_rate_water_equivalent

lssfr

228221


x

61

Instantaneous eastward turbulent surface stress

N m**-2

instantaneous_eastward_turbulent_surface_stress

iews

229

x

x

62

Instantaneous northward turbulent surface stress

N m**-2

instantaneous_northward_turbulent_surface_stress

inss

230

x

x

63

Instantaneous surface sensible heat flux

W m**-2

instantaneous_surface_sensible_heat_flux

ishf

231

x

x

64

Instantaneous moisture flux

kg m**-2 s**-1

instantaneous_moisture_flux

ie

232

x

x

65

Skin temperature

K

skin_temperature

skt

235

x

x

66

Soil temperature level 41

K

soil_temperature_level_4

stl4

236

x

x

67

Temperature of snow layer

K

temperature_of_snow_layer

tsn

238

x

x

68

Forecast albedo

(0 - 1)

forecast_albedo

fal

243

x

x

69

Forecast surface roughness

m

forecast_surface_roughness

fsr

244

x

x

70

Forecast logarithm of surface roughness for heat

~

forecast_logarithm_of_surface_roughness_for_heat

flsr

245

x

x

71

100 metre U wind component

m s**-1

100m_u_component_of_wind

100u

228246

x

x

72

100 metre V wind component

m s**-1

100m_v_component_of_wind

100v

228247

x

x

73

Precipitation type

code table (4.201)

precipitation_type

ptype

260015*


x

74

K index

K

k_index

kx

260121*


x

75

Total totals index

K

total_totals_index

totalx

260123*


x

1

 Soil layers
LayerRange
Layer 10 - 7 cm
Layer 27 - 28 cm
Layer 328 - 100 cm
Layer 4100 - 289 cm

*GRIB2 format


Table 3: stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc: surface and single level parameters: accumulations

count

name

units

Variable name in CDS

shortName

paramId

an

fc

1

Large-scale precipitation fraction

s

large_scale_precipitation_fraction

lspf

50


x

2

Downward UV radiation at the surface

J m**-2

downward_uv_radiation_at_the_surface

uvb

57


x

3

Boundary layer dissipation

J m**-2

boundary_layer_dissipation

bld

145


x

4

Surface sensible heat flux

J m**-2

surface_sensible_heat_flux

sshf

146


x

5

Surface latent heat flux

J m**-2

surface_latent_heat_flux

slhf

147


x

6

Surface solar radiation downwards

J m**-2

surface_solar_radiation_downwards

ssrd

169


x

7

Surface thermal radiation downwards

J m**-2

surface_thermal_radiation_downwards

strd

175


x

8

Surface net solar radiation

J m**-2

surface_net_solar_radiation

ssr

176


x

9

Surface net thermal radiation

J m**-2

surface_net_thermal_radiation

str

177


x

10

Top net solar radiation

J m**-2

top_net_solar_radiation

tsr

178


x

11

Top net thermal radiation

J m**-2

top_net_thermal_radiation

ttr

179


x

12

Eastward turbulent surface stress

N m**-2 s

eastward_turbulent_surface_stress

ewss

180


x

13

Northward turbulent surface stress

N m**-2 s

northward_turbulent_surface_stress

nsss

181


x

14

Eastward gravity wave surface stress

N m**-2 s

eastward_gravity_wave_surface_stress

lgws

195


x

15

Northward gravity wave surface stress

N m**-2 s

northward_gravity_wave_surface_stress

mgws

196


x

16

Gravity wave dissipation

J m**-2

gravity_wave_dissipation

gwd

197


x

17

Top net solar radiation, clear sky

J m**-2

top_net_solar_radiation_clear_sky

tsrc

208


x

18

Top net thermal radiation, clear sky

J m**-2

top_net_thermal_radiation_clear_sky

ttrc

209


x

19

Surface net solar radiation, clear sky

J m**-2

surface_net_solar_radiation_clear_sky

ssrc

210


x

20

Surface net thermal radiation, clear sky

J m**-2

surface_net_thermal_radiation_clear_sky

strc

211


x

21

TOA incident solar radiation

J m**-2

toa_incident_solar_radiation

tisr

212


x

22

Vertically integrated moisture divergence

kg m**-2

vertically_integrated_moisture_divergence

vimd

213


x

23

Total sky direct solar radiation at surface

J m**-2

total_sky_direct_solar_radiation_at_surface

fdir

228021


x

24

Clear-sky direct solar radiation at surface

J m**-2

clear_sky_direct_solar_radiation_at_surface

cdir

228022


x

25

Surface solar radiation downward clear-sky

J m**-2

surface_solar_radiation_downward_clear_sky

ssrdc

228129


x

26

Surface thermal radiation downward clear-sky

J m**-2

surface_thermal_radiation_downward_clear_sky

strdc

228130


x

27

Surface runoff

m

surface_runoff

sro

8


x

28

Sub-surface runoff

m

sub_surface_runoff

ssro

9


x

29

Snow evaporation

m of water equivalent

snow_evaporation

es

44


x

30

Snowmelt

m of water equivalent

snowmelt

smlt

45


x

31

Large-scale precipitation

m

large_scale_precipitation

lsp

142


x

32

Convective precipitation

m

convective_precipitation

cp

143


x

33

Snowfall

m of water equivalent

snowfall

sf

144


x

34

Evaporation

m of water equivalent

evaporation

e

182


x

35

Runoff

m

runoff

ro

205


x

36

Total precipitation

m

total_precipitation

tp

228


x

37

Convective snowfall

m of water equivalent

convective_snowfall

csf

239


x

38

Large-scale snowfall

m of water equivalent

large_scale_snowfall

lsf

240


x

39

Potential evaporation

m

potential_evaporation

pev

228251


x

Accumulations are described in section Mean rates and accumulations. The accumulations in monthly means of daily means (stream=moda/edmo) have been scaled to have units that include "per day", so for accumulations in these streams:

  • The hydrological parameters are in units of "m of water per day" and so they should be multiplied by 1000 to convert to kg m-2 day-1 or mm day-1.
  • Energy (turbulent and radiative) and momentum fluxes should be divided by 86400 seconds (24 hours) to convert to the commonly used units of W m-2 and N m-2, respectively.


 Table 4: stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc: surface and single level parameters: mean rates

countnameunitsVariable name in CDSshortNameparamIdanfc
1

Mean surface runoff rate

kg m**-2 s**-1

mean_surface_runoff_rate

msror

235020


x
2

Mean sub-surface runoff rate

kg m**-2 s**-1

mean_sub_surface_runoff_rate

mssror

235021


x
3

Mean snow evaporation rate

kg m**-2 s**-1

mean_snow_evaporation_rate

mser

235023


x
4

Mean snowmelt rate

kg m**-2 s**-1

mean_snowmelt_rate

msmr

235024


x
5

Mean large-scale precipitation fraction

Proportion

mean_large_scale_precipitation_fraction

mlspf

235026


x
6

Mean surface downward UV radiation flux

W m**-2

mean_surface_downward_uv_radiation_flux

msdwuvrf

235027


x
7

Mean large-scale precipitation rate

kg m**-2 s**-1

mean_large_scale_precipitation_rate

mlspr

235029


x
8

Mean convective precipitation rate

kg m**-2 s**-1

mean_convective_precipitation_rate

mcpr

235030


x
9

Mean snowfall rate

kg m**-2 s**-1

mean_snowfall_rate

msr

235031


x
10

Mean boundary layer dissipation

W m**-2

mean_boundary_layer_dissipation

mbld

235032


x
11

Mean surface sensible heat flux

W m**-2

mean_surface_sensible_heat_flux

msshf

235033


x
12

Mean surface latent heat flux

W m**-2

mean_surface_latent_heat_flux

mslhf

235034


x
13

Mean surface downward short-wave radiation flux

W m**-2

mean_surface_downward_short_wave_radiation_flux

msdwswrf

235035


x
14

Mean surface downward long-wave radiation flux

W m**-2

mean_surface_downward_long_wave_radiation_flux

msdwlwrf

235036


x
15

Mean surface net short-wave radiation flux

W m**-2

mean_surface_net_short_wave_radiation_flux

msnswrf

235037


x
16

Mean surface net long-wave radiation flux

W m**-2

mean_surface_net_long_wave_radiation_flux

msnlwrf

235038


x
17

Mean top net short-wave radiation flux

W m**-2

mean_top_net_short_wave_radiation_flux

mtnswrf

235039


x
18

Mean top net long-wave radiation flux

W m**-2

mean_top_net_long_wave_radiation_flux

mtnlwrf

235040


x
19

Mean eastward turbulent surface stress

N m**-2

mean_eastward_turbulent_surface_stress

metss

235041


x
20

Mean northward turbulent surface stress

N m**-2

mean_northward_turbulent_surface_stress

mntss

235042


x
21

Mean evaporation rate

kg m**-2 s**-1

mean_evaporation_rate

mer

235043


x
22

Mean eastward gravity wave surface stress

N m**-2

mean_eastward_gravity_wave_surface_stress

megwss

235045


x
23

Mean northward gravity wave surface stress

N m**-2

mean_northward_gravity_wave_surface_stress

mngwss

235046


x
24

Mean gravity wave dissipation

W m**-2

mean_gravity_wave_dissipation

mgwd

235047


x
25

Mean runoff rate

kg m**-2 s**-1

mean_runoff_rate

mror

235048


x
26

Mean top net short-wave radiation flux, clear sky

W m**-2

mean_top_net_short_wave_radiation_flux_clear_sky

mtnswrfcs

235049


x
27

Mean top net long-wave radiation flux, clear sky

W m**-2

mean_top_net_long_wave_radiation_flux_clear_sky

mtnlwrfcs

235050


x
28

Mean surface net short-wave radiation flux, clear sky

W m**-2

mean_surface_net_short_wave_radiation_flux_clear_sky

msnswrfcs

235051


x
29

Mean surface net long-wave radiation flux, clear sky

W m**-2

mean_surface_net_long_wave_radiation_flux_clear_sky

msnlwrfcs

235052


x
30

Mean top downward short-wave radiation flux

W m**-2

mean_top_downward_short_wave_radiation_flux

mtdwswrf

235053


x
31

Mean vertically integrated moisture divergence

kg m**-2 s**-1

mean_vertically_integrated_moisture_divergence

mvimd

235054


x
32

Mean total precipitation rate

kg m**-2 s**-1

mean_total_precipitation_rate

mtpr

235055


x
33

Mean convective snowfall rate

kg m**-2 s**-1

mean_convective_snowfall_rate

mcsr

235056


x
34

Mean large-scale snowfall rate

kg m**-2 s**-1

mean_large_scale_snowfall_rate

mlssr

235057


x
35

Mean surface direct short-wave radiation flux

W m**-2

mean_surface_direct_short_wave_radiation_flux

msdrswrf

235058


x
36

Mean surface direct short-wave radiation flux, clear sky

W m**-2

mean_surface_direct_short_wave_radiation_flux_clear_sky

msdrswrfcs

235059


x
37

Mean surface downward short-wave radiation flux, clear sky

W m**-2

mean_surface_downward_short_wave_radiation_flux_clear_sky

msdwswrfcs

235068


x
38

Mean surface downward long-wave radiation flux, clear sky

W m**-2

mean_surface_downward_long_wave_radiation_flux_clear_sky

msdwlwrfcs

235069


x
39

Mean potential evaporation rate

kg m**-2 s**-1

mean_potential_evaporation_rate

mper

235070


x

The mean rates in Table 4 provide similar information to the accumulations in Table 3, except that they are expressed as temporal averages instead of accumulations, and so have units of "per second". The hydrological parameters are in units of "kg m-2 s-1" and so they can be multiplied by 86400 seconds (24 hours) to convert to kg m-2 day-1 or mm day-1.


Table 5: stream=oper/enda, levtype=sfc: surface and single level parameters: minimum/maximum

count

name

units

Variable name in CDS

shortName

paramId

an

fc

1

10 metre wind gust since previous post-processing

m s**-1

10m_wind_gust_since_previous_post_processing

10fg

49


x

2

Maximum temperature at 2 metres since previous post-processing

K

maximum_2m_temperature_since_previous_post_processing

mx2t

201


x

3

Minimum temperature at 2 metres since previous post-processing

K

minimum_2m_temperature_since_previous_post_processing

mn2t

202


x

4

Maximum total precipitation rate since previous post-processing

kg m**-2 s**-1

maximum_total_precipitation_rate_since_previous_post_processing

mxtpr

228226


x

5

Minimum total precipitation rate since previous post-processing

kg m**-2 s**-1

minimum_total_precipitation_rate_since_previous_post_processing

mntpr

228227


x



Table 6: stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc: surface and single level parameters: vertical integrals (not available for type=em/es) and total column: instantaneous

count

name

units

Variable name in CDS

shortName

paramId

an

fc

1

Vertical integral of mass of atmosphere

kg m**-2

vertical_integral_of_mass_of_atmosphere

vima

162053

x

x

2

Vertical integral of temperature

K kg m**-2

vertical_integral_of_temperature

vit

162054

x

x

3

Vertical integral of kinetic energy

J m**-2

vertical_integral_of_kinetic_energy

vike

162059

x

x

4

Vertical integral of thermal energy

J m**-2

vertical_integral_of_thermal_energy

vithe

162060

x

x

5

Vertical integral of potential+internal energy

J m**-2

vertical_integral_of_potential_and_internal_energy

vipie

162061

x

x

6

Vertical integral of potential+internal+latent energy

J m**-2

vertical_integral_of_potential_internal_and_latent_energy

vipile

162062

x

x

7

Vertical integral of total energy

J m**-2

vertical_integral_of_total_energy

vitoe

162063

x

x

8

Vertical integral of energy conversion

W m**-2

vertical_integral_of_energy_conversion

viec

162064

x

x

9

Vertical integral of eastward mass flux

kg m**-1 s**-1

vertical_integral_of_eastward_mass_flux

vimae

162065

x

x

10

Vertical integral of northward mass flux

kg m**-1 s**-1

vertical_integral_of_northward_mass_flux

viman

162066

x

x

11

Vertical integral of eastward kinetic energy flux

W m**-1

vertical_integral_of_eastward_kinetic_energy_flux

vikee

162067

x

x

12

Vertical integral of northward kinetic energy flux

W m**-1

vertical_integral_of_northward_kinetic_energy_flux

viken

162068

x

x

13

Vertical integral of eastward heat flux

W m**-1

vertical_integral_of_eastward_heat_flux

vithee

162069

x

x

14

Vertical integral of northward heat flux

W m**-1

vertical_integral_of_northward_heat_flux

vithen

162070

x

x

15

Vertical integral of eastward water vapour flux

kg m**-1 s**-1

vertical_integral_of_eastward_water_vapour_flux

viwve

162071

x

x

16

Vertical integral of northward water vapour flux

kg m**-1 s**-1

vertical_integral_of_northward_water_vapour_flux

viwvn

162072

x

x

17

Vertical integral of eastward geopotential flux

W m**-1

vertical_integral_of_eastward_geopotential_flux

vige

162073

x

x

18

Vertical integral of northward geopotential flux

W m**-1

vertical_integral_of_northward_geopotential_flux

vign

162074

x

x

19

Vertical integral of eastward total energy flux

W m**-1

vertical_integral_of_eastward_total_energy_flux

vitoee

162075

x

x

20

Vertical integral of northward total energy flux

W m**-1

vertical_integral_of_northward_total_energy_flux

vitoen

162076

x

x

21

Vertical integral of eastward ozone flux

kg m**-1 s**-1

vertical_integral_of_eastward_ozone_flux

vioze

162077

x

x

22

Vertical integral of northward ozone flux

kg m**-1 s**-1

vertical_integral_of_northward_ozone_flux

viozn

162078

x

x

23

Vertical integral of divergence of cloud liquid water flux

kg m**-2 s**-1

vertical_integral_of_divergence_of_cloud_liquid_water_flux

vilwd

162079

x

x

24

Vertical integral of divergence of cloud frozen water flux

kg m**-2 s**-1

vertical_integral_of_divergence_of_cloud_frozen_water_flux

viiwd

162080

x

x

25

Vertical integral of divergence of mass flux

kg m**-2 s**-1

vertical_integral_of_divergence_of_mass_flux

vimad

162081

x

x

26

Vertical integral of divergence of kinetic energy flux

W m**-2

vertical_integral_of_divergence_of_kinetic_energy_flux

viked

162082

x

x

27

Vertical integral of divergence of thermal energy flux

W m**-2

vertical_integral_of_divergence_of_thermal_energy_flux

vithed

162083

x

x

28

Vertical integral of divergence of moisture flux

kg m**-2 s**-1

vertical_integral_of_divergence_of_moisture_flux

viwvd

162084

x

x

29

Vertical integral of divergence of geopotential flux

W m**-2

vertical_integral_of_divergence_of_geopotential_flux

vigd

162085

x

x

30

Vertical integral of divergence of total energy flux

W m**-2

vertical_integral_of_divergence_of_total_energy_flux

vitoed

162086

x

x

31

Vertical integral of divergence of ozone flux

kg m**-2 s**-1

vertical_integral_of_divergence_of_ozone_flux

viozd

162087

x

x

32

Vertical integral of eastward cloud liquid water flux

kg m**-1 s**-1

vertical_integral_of_eastward_cloud_liquid_water_flux

vilwe

162088

x

x

33

Vertical integral of northward cloud liquid water flux

kg m**-1 s**-1

vertical_integral_of_northward_cloud_liquid_water_flux

vilwn

162089

x

x

34

Vertical integral of eastward cloud frozen water flux

kg m**-1 s**-1

vertical_integral_of_eastward_cloud_frozen_water_flux

viiwe

162090

x

x

35

Vertical integral of northward cloud frozen water flux

kg m**-1 s**-1

vertical_integral_of_northward_cloud_frozen_water_flux

viiwn

162091

x

x

36

Vertical integral of mass tendency

kg m**-2 s**-1

vertical_integral_of_mass_tendency

vimat

162092

x


37

Total column cloud liquid water

kg m**-2

total_column_cloud_liquid_water

tclw

78

x

x

38

Total column cloud ice water

kg m**-2

total_column_cloud_ice_water

tciw

79

x

x

39

Total column supercooled liquid water

kg m**-2

total_column_supercooled_liquid_water

tcslw

228088


x

40

Total column rain water

kg m**-2

total_column_rain_water

tcrw

228089

x

x

41

Total column snow water

kg m**-2

total_column_snow_water

tcsw

228090

x

x

42

Total column water

kg m**-2

total_column_water

tcw

136

x

x

43

Total column water vapour

kg m**-2

total_column_water_vapour

tcwv

137

x

x

44

Total column ozone

kg m**-2

total_column_ozone

tco3

206

x

x



Table 7: stream=wave/ewda/wamo/wamd/ewmm/ewmo: wave parameters: instantaneous

count

name

units

Variable name in CDS

shortName

paramId

an

fc

1

Significant wave height of first swell partition

m

significant_wave_height_of_first_swell_partition

swh1

140121

x

x

2

Mean wave direction of first swell partition

degrees

mean_wave_direction_of_first_swell_partition

mwd1

140122

x

x

3

Mean wave period of first swell partition

s

mean_wave_period_of_first_swell_partition

mwp1

140123

x

x

4

Significant wave height of second swell partition

m

significant_wave_height_of_second_swell_partition

swh2

140124

x

x

5

Mean wave direction of second swell partition

degrees

mean_wave_period_of_second_swell_partition

mwd2

140125

x

x

6

Mean wave period of second swell partition

s

mean_wave_period_of_second_swell_partition

mwp2

140126

x

x

7

Significant wave height of third swell partition

m

significant_wave_height_of_third_swell_partition

swh3

140127

x

x

8

Mean wave direction of third swell partition

degrees

mean_wave_direction_of_third_swell_partition

mwd3

140128

x

x

9

Mean wave period of third swell partition

s

mean_wave_period_of_third_swell_partition

mwp3

140129

x

x

10

Wave Spectral Skewness

dimensionless

wave_spectral_skewness

wss

140207

x

x

11

Free convective velocity over the oceans

m s**-1

free_convective_velocity_over_the_oceans

wstar

140208

x

x

12

Air density over the oceans

kg m**-3

air_density_over_the_oceans

rhoao

140209

x

x

13

Normalized energy flux into waves

dimensionless

normalized_energy_flux_into_waves

phiaw

140211

x

x

14

Normalized energy flux into ocean

dimensionless

normalized_energy_flux_into_ocean

phioc

140212

x

x

15

Normalized stress into ocean

dimensionless

normalized_stress_into_ocean

tauoc

140214

x

x

16

U-component stokes drift

m s**-1

u_component_stokes_drift

ust

140215

x

x

17

V-component stokes drift

m s**-1

v_component_stokes_drift

vst

140216

x

x

18

Period corresponding to maximum individual wave height

s

period_corresponding_to_maximum_individual_wave_height

tmax

140217

x

x

19

Maximum individual wave height

m

maximum_individual_wave_height

hmax

140218

x

x

20

Model bathymetry

m

model_bathymetry

wmb

140219

x

x

21

Mean wave period based on first moment

s

mean_wave_period_based_on_first_moment

mp1

140220

x

x

22

Mean zero-crossing wave period

s

mean_zero_crossing_wave_period

mp2

140221

x

x

23

Wave spectral directional width

dimensionless

wave_spectral_directional_width

wdw

140222

x

x

24

Mean wave period based on first moment for wind waves

s

mean_wave_period_based_on_first_moment_for_wind_waves

p1ww

140223

x

x

25

Mean wave period based on second moment for wind waves

s

mean_wave_period_based_on_second_moment_for_wind_waves

p2ww

140224

x

x

26

Wave spectral directional width for wind waves

dimensionless

wave_spectral_directional_width_for_wind_waves

dwww

140225

x

x

27

Mean wave period based on first moment for swell

s

mean_wave_period_based_on_first_moment_for_swell

p1ps

140226

x

x

28

Mean wave period based on second moment for swell

s

mean_wave_period_based_on_second_moment_for_wind_waves

p2ps

140227

x

x

29

Wave spectral directional width for swell

dimensionless

wave_spectral_directional_width_for_swell

dwps

140228

x

x

30

Significant height of combined wind waves and swell

m

significant_height_of_combined_wind_waves_and_swell

swh

140229

x

x

31

Mean wave direction

degrees

mean_wave_direction

mwd

140230

x

x

32

Peak wave period

s

peak_wave_period

pp1d

140231

x

x

33

Mean wave period

s

mean_wave_period

mwp

140232

x

x

34

Coefficient of drag with waves

dimensionless

coefficient_of_drag_with_waves

cdww

140233

x

x

35

Significant height of wind waves

m

significant_height_of_wind_waves

shww

140234

x

x

36

Mean direction of wind waves

degrees

mean_direction_of_wind_waves

mdww

140235

x

x

37

Mean period of wind waves

s

mean_period_of_wind_waves

mpww

140236

x

x

38

Significant height of total swell

m

significant_height_of_total_swell

shts

140237

x

x

39

Mean direction of total swell

degrees

mean_direction_of_total_swell

mdts

140238

x

x

40

Mean period of total swell

s

mean_period_of_total_swell

mpts

140239

x

x

41

Mean square slope of waves

dimensionless

mean_square_slope_of_waves

msqs

140244

x

x

42

 10 metre wind speed

This 10m wind parameter is the wind speed that has been used by the wave model, which is coupled to the atmospheric model.

For this reason:

  •  it is archived on the wave model's native grid, with the same land-sea mask as that model. Therefore, this parameter is not defined over land and wherever else the wave model is not defined, where it is encoded as missing data. Improper decoding of the missing value usually results in very large values being given for these land points.
  • the wave model resets all values below 2 m/s to 2m/s. The reason for this is that as the winds become weak, the long waves (swell) try to drive the wind from below but this is not modelled in the IFS, as it assumes that the wind profile should be logarithmic (+- stability correction). To account for this effect, the whole of the boundary layer scheme would need to be revised. A simple trick to avoid the problem is to boost the weak winds to 2m/s, which is outside the range where the waves can potentially drive the wind.
  • this parameter is actually the 10m neutral wind speed as determined from the atmospheric surface stress (see documentation on Ocean Wave model output parameters).  
  • If wave altimeter data were assimilated, the analysis of this parameter also contains wind speed updates that come directly out of the wave height updates.

This parameter should not be used for looking at the quality of reanalysis surface wind - the u and v components of the 10m wind (atmospheric parameters 165 and 166) should be used instead.

m s**-1

ocean_surface_stress_equivalent_10m_neutral_wind_speed

wind

140245

x

x

43

Altimeter wave height

m

altimeter_wave_height

awh

140246

x


44

Altimeter corrected wave height

m

altimeter_corrected_wave_height

acwh

140247

x


45

Altimeter range relative correction

~

altimeter_range_relative_correction

arrc

140248

x


46

10 metre wind direction

degrees

ocean_surface_stress_equivalent_10m_neutral_wind_direction

dwi

140249

x

x

47

Wave spectral kurtosis

dimensionless

wave_spectral_kurtosis

wsk

140252

x

x

48

Benjamin-Feir index

dimensionless

benjamin_feir_index

bfi

140253

x

x

49

Wave spectral peakedness

dimensionless

wave_spectral_peakedness

wsp

140254

x

x

50

2D wave spectra (single)

m**2 s radian**-1


2dfd

140251*

x


*for 30 frequencies and 24 directions


Table 8: stream=mnth/moda/edmm/edmo, levtype=sfc or wamo/wamd/ewmm/ewmo: monthly mean surface and single level and wave parameters: exceptions from Tables 1-7

count

name

units

Variable name in CDS

shortName

paramId

an

fc

1

UV visible albedo for direct radiation

(0 - 1)

uv_visible_albedo_for_direct_radiation

aluvp

15

x

no mean

2

UV visible albedo for diffuse radiation

(0 - 1)

uv_visible_albedo_for_diffuse_radiation

aluvd

16

x

no mean

3

Near IR albedo for direct radiation

(0 - 1)

near_ir_albedo_for_direct_radiation

alnip

17

x

no mean

4

Near IR albedo for diffuse radiation

(0 - 1)

near_ir_albedo_for_diffuse_radiation

alnid

18

x

no mean

5

Magnitude of turbulent surface stress

N m**-2 s


magss

48


x

6Mean magnitude of turbulent surface stressN m**-2
mmtss235025
x

7

10 metre wind gust since previous post-processing

m s**-1

10m_wind_gust_since_previous_post_processing

10fg

49


no mean

8

Maximum temperature at 2 metres since previous post-processing

K

maximum_2m_temperature_since_previous_post_processing

mx2t

201


no mean

9

Minimum temperature at 2 metres since previous post-processing

K

minimum_2m_temperature_since_previous_post_processing

mn2t

202


no mean

10

10 metre wind speed

m s**-1


10si

207

x

x

11

Maximum total precipitation rate since previous post-processing

kg m**-2 s**-1

maximum_total_precipitation_rate_since_previous_post_processing

mxtpr

228226


no mean

12

Minimum total precipitation rate since previous post-processing

kg m**-2 s**-1

minimum_total_precipitation_rate_since_previous_post_processing

mntpr

228227


no mean

13

Altimeter wave height

m

altimeter_wave_height

awh

140246

no mean


14

Altimeter corrected wave height

m

altimeter_corrected_wave_height

acwh

140247

no mean


15

Altimeter range relative correction

~

altimeter_range_relative_correction

arrc

140248

no mean


16

2D wave spectra (single)

m**2 s radian**-1


2dfd

140251

no mean



Table 9: stream=oper/enda/mnth/moda/edmm/edmo, levtype=pl: pressure level parameters: instantaneous

count

name

units

Variable name in CDS

shortName

paramId

an

fc

1

Potential vorticity

K m**2 kg**-1 s**-1

potential_vorticity

pv

60

x

x

2

Specific rain water content

kg kg**-1

specific_rain_water_content

crwc

75

x

x

3

Specific snow water content

kg kg**-1

specific_snow_water_content

cswc

76

x

x

4

Geopotential

m**2 s**-2

geopotential

z

129

x

x

5

Temperature

K

temperature

t

130

x

x

6

U component of wind

m s**-1

u_component_of_wind

u

131

x

x

7

V component of wind

m s**-1

v_component_of_wind

v

132

x

x

8

Specific humidity

kg kg**-1

specific_humidity

q

133

x

x

9

Vertical velocity

Pa s**-1

vertical_velocity

w

135

x

x

10

Vorticity (relative)

s**-1

vorticity

vo

138

x

x

11

Divergence

s**-1

divergence

d

155

x

x

12

Relative humidity

%

relative_humidity

r

157

x

x

13

Ozone mass mixing ratio

kg kg**-1

ozone_mass_mixing_ratio

o3

203

x

x

14

Specific cloud liquid water content

kg kg**-1

specific_cloud_liquid_water_content

clwc

246

x

x

15

Specific cloud ice water content

kg kg**-1

specific_cloud_ice_water_content

ciwc

247

x

x

16

Fraction of cloud cover

(0 - 1)

fraction_of_cloud_cover

cc

248

x

x


Table 10: stream=oper/enda/mnth/moda/edmm/edmo, levtype=pt: potential temperature level parameters: instantaneous

count

name

units

shortName

paramId

an

fc

1

Montgomery potential

m**2 s**-2

mont

53

x


2

Pressure

Pa

pres

54

x


3

Potential vorticity

K m**2 kg**-1 s**-1

pv

60

x


4

U component of wind

m s**-1

u

131

x


5

V component of wind

m s**-1

v

132

x


6

Specific humidity

kg kg**-1

q

133

x


7

Vorticity (relative)

s**-1

vo

138

x


8

Divergence

s**-1

d

155

x


9

Ozone mass mixing ratio

kg kg**-1

o3

203

x




Table 11: stream=oper/enda/mnth/moda/edmm/edmo, levtype=pv: potential vorticity level parameters: instantaneous

count

name

units

shortName

paramId

an

fc

1

Potential temperature

K

pt

3

x


2

Pressure

Pa

pres

54

x


3

Geopotential

m**2 s**-2

z

129

x


4

U component of wind

m s**-1

u

131

x


5

V component of wind

m s**-1

v

132

x


6

Specific humidity

kg kg**-1

q

133

x


7

Ozone mass mixing ratio

kg kg**-1

o3

203

x




Table 12: stream=oper/enda/mnth/moda/edmm/edmo, levtype=ml: model level parameters: instantaneous

count

name

units

shortName

paramId

an

fc

1

Specific rain water content

kg kg**-1

crwc

75

x

x

2

Specific snow water content

kg kg**-1

cswc

76

x

x

3

Eta-coordinate vertical velocity

s**-1

etadot

77

x

x

4

Geopotential*

m**2 s**-2

z

129

x

x

5

Temperature

K

t

130

x

x

6

U component of wind

m s**-1

u

131

x

x

7

V component of wind

m s**-1

v

132

x

x

8

Specific humidity

kg kg**-1

q

133

x

x

9

Vertical velocity

Pa s**-1

w

135

x

x

10

Vorticity (relative)

s**-1

vo

138

x

x

11

Logarithm of surface pressure*

~

lnsp

152

x

x

12

Divergence

s**-1

d

155

x

x

13

Ozone mass mixing ratio

kg kg**-1

o3

203

x

x

14

Specific cloud liquid water content

kg kg**-1

clwc

246

x

x

15

Specific cloud ice water content

kg kg**-1

ciwc

247

x

x

16

Fraction of cloud cover

(0 - 1)

cc

248

x

x

*Only archived on level=1.


Table 13: stream=oper/enda/mnth/moda/edmm/edmo, levtype=ml: model level parameters: mean rates

countnameunitsshortNameparamIdanfc
1Mean temperature tendency due to short-wave radiationK s**-1mttswr235001
x
2Mean temperature tendency due to long-wave radiationK s**-1mttlwr235002
x
3Mean temperature tendency due to short-wave radiation, clear skyK s**-1mttswrcs235003
x
4Mean temperature tendency due to long-wave radiation, clear skyK s**-1mttlwrcs235004
x
5Mean temperature tendency due to parametrisationsK s**-1mttpm235005
x
6Mean specific humidity tendency due to parametrisationskg kg**-1 s**-1mqtpm235006
x
7Mean eastward wind tendency due to parametrisationsm s**-2mutpm235007
x
8Mean northward wind tendency due to parametrisationsm s**-2mvtpm235008
x
9Mean updraught mass flux*kg m**-2 s**-1mumf235009
x
10Mean downdraught mass flux*kg m**-2 s**-1mdmf235010
x
11Mean updraught detrainment ratekg m**-3 s**-1mudr235011
x
12Mean downdraught detrainment ratekg m**-3 s**-1mddr235012
x
13Mean total precipitation flux*kg m**-2 s**-1mtpf235013
x
14Mean turbulent diffusion coefficient for heat*m**2 s**-1mtdch235014
x

*These parameters provide data for the model half levels, at the interfaces of the model layers.

Observations

The observations (satellite and in-situ) used as input into ERA5 are listed below.

Satellite Data

SensorSatelliteSatellite agencyData provider+

Measurement

(sensitivities exploited in ERA5 / variables analysed)

Satellite radiances (infrared and microwave)



AIRSAQUANASANOAABT (T, humidity and ozone)
AMSR-2GCOM-W1*JAXA

BT  (column water vapour, cloud liquid water,

precipitation and ocean surface wind speed)

AMSREAQUA*JAXA

BT  (column water vapour, cloud liquid water,

precipitation and ocean surface wind speed)

AMSUANOAA-15/16/17/18/19, AQUA, METOP-A/BNOAA,ESA,EUMETSAT
BT (T)
AMSUBNOAA-15/16/17NOAA
BT (humidity)
ATMSNPPNOAA
BT (T and humidity)
CRISNPPNOAA
BT (T, humidity and ozone)
HIRSTIROS-N, NOAA-6 /7/8/9/11/14NOAA
BT (T, humidity and ozone)
IASIMETOP-A/BEUMETSAT/ESAEUMETSATBT (T, humidity and ozone)
GMIGPMNASA/JAXA

BT (humidity, column water vapour,

cloud liquid water, precipitation,

ocean surface wind speed)

MHSNOAA-18/19, METOP-A/BNOAA, EUMETSAT/ESA
BT (humidity and precipitation)
MSUTIROS-N, NOAA-6 to 12, NOAA-14

BT (T)
MWHSFY-3-A/BNRSCC
BT (humidity)
MWHS2FY-3-CCMA
BT (T, humidity and precipitation)
MWTSFY-3A/BNRSCC
BT (T)
MWTS2FY-3CCMA
BT (T)
SSM/IDMSP-08*/10*/11*/13*/14*/15*US NavyNOAA,CMSAF*

BT (column water vapour, cloud liquid water,

precipitation and ocean surface wind speed)

SSMISDMSP-16/17/18US NavyNOAA

BT (T,  humidity,  column water vapour,

cloud liquid water, precipitation and ocean surface wind speed)

SSUTIROS-N, NOAA-6/7/8/9/11/14NOAA
BT (T)
TMITRMMNASA/JAXA
BT (column water vapour, cloud liquid water,

precipitation, ocean surface wind speed)

MVIRIMETEOSAT 5/7EUMETSAT/ESAEUMETSATBT (water vapour, surface/cloud top T)
SEVIRIMETEOSAT-8*/9*/10EUMETSAT/ESAEUMETSATBT (water vapour, surface/cloud top T)
GOES IMAGERGOES-8/9/10/11/12/13/15NOAACIMMS,NESDISBT (water vapour, surface/cloud top T)
MTSAT IMAGERMTSAT-1R/MTSAT-2JMA
BT (water vapour, surface/cloud top T)
AHIHimawari-8JMA
BT (water vapour, surface/cloud top T)
Satellite retrievals from radiance data



MVIRIMETEOSAT-2*/3*/4*/5*/7*EUMETSAT/ESAEUMETSATwind vector
SEVIRIMETEOSAT-8*/9*/10EUMETSAT/ESAEUMETSATwind vector
GOES IMAGERGOES-4-6/8*/9*/10*/11*/12*/13*/15*NOAACIMMS*,NESDISwind vector
GMS IMAGERGMS-1*/2/3*/4*/5*JMA
wind vector
MTSAT IMAGERMTSAT-1R*/MTSAT2JMA
wind vector
AHIHimawari-8JMAJMAwind vector
AVHRRNOAA-7 /9/10/11/12/14 to 18, METOP-ANOAACIMMS,EUMETSATwind vector
MODISAQUA/TERRANASANESDIS,CIMMSwind vector
GOMEERS-2*ESA
Ozone
GOME-2METOP*-A/BESA/EUMETSAT
Ozone
MIPASENVISAT*ESA
Ozone
MLSEOS-AURA*NASA
Ozone
OMIEOS-AURA*NASA
Ozone
SBUV,SBUV-2NIMBUS-7*,NOAA*9/11/14/16/17/18/19NOAANASAOzone
SCIAMACHYENVISAT*ESA
Ozone
TOMSNIMBUS-7*,METEOR-3-5,ADEOS-1*,EARTH PROBENASA
Ozone
Satellite GPS-Radio Occultation data



BlackJackCHAMP,GRACE*-A/B,SAC-C*DLR,NASA/DLR,NASA/COMAEGFZ,UCAR*Bending angle
GRASMETOP-A/BEUMETSAT/ESAEUMETSATBending angle
IGORTerraSAR-X*, TanDEM-X, COSMIC*-1 to 6NSPO/NOAAGFZ,UCAR*Bending angle
Satellite scatterometer data



AMIERS-1,ERS-2ESA
Backscatter sigma0, soil moisture
ASCATMETOP-A/B*EUMETSAT/ESAEUMETSAT/TU WienBackscatter sigma0, soil moisture
OSCATOCEANSAT-2ISROKNMIBackscatter sigma0, vector wind
SEAWINDSQUIKSCATNASANASABackscatter sigma0
Satellite Altimeter data



RAERS-1*/2*ESA
Wave Height
RA-2ENVISAT*ESA
Wave Height
Poseidon-2JASON-1*CNES/NASACNESWave Height
Poseidon-3JASON-2CNES/NOAA/NASA/EUMETSATNOAA/EUMETSATWave Height
SIRALCRYOSAT-2ESA
Wave Height
AltiKaSARALCNES/ISROEUMETSATWave Height

* reprocessed dataset
+ when different than the satellite agency

In-situ data, provided by WMO WIS

Dataset nameObservation typeMeasurement
SYNOPLand stationSurface Pressure, Temperature, wind, humidity
METARLand stationSurface Pressure, Temperature, wind,humidity
DRIBU/DRIBU-BATHY/DRIBU-TESAC/BUFR Drifting BuoyDrifting buoys10m-wind, Surface Pressure
BUFR Moored BuoyMoored buoys10m-wind, Surface Pressure
SHIPship stationSurface Pressure, Temperature, wind, humidity
Land/ship PILOTRadiosondeswind profiles
American Wind ProfilerRadarwind profiles
European Wind ProfilerRadarwind profiles
Japanese Wind ProfilerRadarwind profiles
TEMP SHIPRadiosondesTemperature, wind, humidity profiles
DROP SondeAircraft-sondesTemperature, wind profiles
Land/Mobile TEMPRadiosondesTemperature, wind, humidity profiles
AIREPAircraft dataTemperature, wind profiles
AMDARAircraft dataTemperature, wind profiles
ACARSAircraft dataTemperature, wind profiles, humidity
WIGOS AMDARAircraft dataTemperature, wind profiles
Ground based radarRadar precipitation compositesRain rates

Snow data

Dataset nameObservation typeMeasurement
SYNOPLand stationSnow depth
Additional national reportsLand stationSnow depth
NOAA/NESDIS IMSMerged satelliteSnow cover (NH only)

Computation of near-surface humidity and snow cover

Near-surface humidity

Near-surface humidity is not archived directly in ERA datasets, but the archive contains near-surface (2m from the surface) temperature (T), dew point temperature (Td), and surface pressure[1] (sp) from which you can calculate specific and relative humidity at 2m.

  • Specific humidity can be calculated over water and ice using equations 7.4 and 7.5 from Part IV, Physical processes section (Chapter 7, section 7.2.1b) in the documentation of the IFS for CY41R2. Use the 2m dew point temperature and surface pressure (which is approximately equal to the pressure at 2m) in these equations. The constants in 7.4 are to be found in Chapter 12 (of Part IV: Physical processes) and the parameters in 7.5 should be set for saturation over water because the dew point temperature is being used.
  • Relative humidity should be calculated: RH = 100 * es(Td)/es(T)

 Relative humidity can be calculate with respect to saturation over water, ice or mixed phase by defining es(T) with respect to saturation over water, ice or mixed phase (water and ice). The usual practice is to define near-surface relative humidity with respect to saturation over water.

[1] Access to surface pressure varies by dataset. For example, for ERA-Interim surface pressure is available from the Web Interface and from the WebAPI, while for ERA-40 surface pressure is not available from the Web Interface, but only via the WebAPI.


Snow Cover

In the ECMWF model (IFS), snow is represented by an additional layer on top of the uppermost soil level. The whole grid box may not be covered in snow. The snow cover gives the fraction of the grid box that is covered in snow.

For ERA5, the snow cover (SC) is computed as follows:

ERA5 Snow cover formula

snow_cover (SC) = min(1, (RW*SD/RSN) / 0.1 )

where RW is density of water equal to 1000 and RSN is density of snow (parameter 33.128).


ERA5 physical depth of snow where there is snow cover is equal to RW*SD/(RSN*SC).

Guidelines

The following advice is intended to help users understand particular features of the ERA5 data:

  • Sea surface temperature and sea-ice cover (see Table 2 above) are available at the usual times, eg hourly for the HRES, but their content is only updated once daily.
  • Mean rates and accumulations at step=0 have values of zero because the length of the processing period is zero.

Known issues

Currently, we are aware of these issues with ERA5:

  • ERA5 uncertainty: although small values of ensemble spread correctly mark more confident estimates than large values, numerical values are over confident. The spread does give an indication of the relative uncertainty in space and time.
  • ERA5 suffers from an overly strong equatorial mesospheric jet, particularly in the transition seasons.

  • From 2000 to 2007, ERA5 has a poor fit to radiosonde temperatures in the stratosphere, with a cold bias in the lower stratosphere and a warm bias higher up.

  • Discontinuities in ERA5: ERA5 is produced by several parallel experiments, each for a different period, which are then appended together to create the final product. This can create discontinuities at the transition points.
  • ERA5 diurnal cycle for winds: the hourly data reveals a mismatch in the analysed near surface wind speed between the end of one assimilation cycle and the beginning of the next (which occurs at 9:00 and 21:00 UTC). This problem mostly occurs in low latitude oceanic regions, though it can also be seen over Europe and the USA. The forecast near surface winds show much better agreement between the assimilation cycles, at least on average, so our advice would be to use the forecast winds. We cannot rectify the problem in the analyses.
  • ERA5: large 10m winds: up to a few times per year, the analysed low level winds, eg 10m winds, become very large in a particular location, which varies amongst a few apparently preferred locations. The largest values seen so far are about 300 ms-1.
  • ERA5 rain bombs: from time to time, the rainfall (precipitation) can become extremely large in small areas.
  • Ship tracks in the SST: prior to September 2007, in the period when HadISST2 was used, ship tracks can be visible in the SST.
  • Prior to 2014, the SST was not used over the Great Lakes to nudge the lake model. Consequently, the 2 metre temperature has an annual cycle that is too strong, with temperatures being too cold in winter and too warm in summer.
  • Wind values are far too low on pressure levels at the poles in the Climate Data Store (CDS)
  • The Potential Evaporation field (pev, parameter Id 228251) is largely underestimated over deserts and high-forested areas. This is due to a bug in the code that does not allow transpiration in case no low vegetation type is present.
  • Wave parameters (Table 7 above) for the three swell partitions: these parameters have been calculated incorrectly. The problem is most evident in the swell partition parameters involving the mean wave period: Mean wave period of first swell partition, Mean wave period of second swell partition and Mean wave period of third swell partition, where the periods are far too long.
  • The instantaneous turbulent surface stress components (eastward and northward) and friction velocity tend to be too small.

Resolved issues

How to cite ERA5

Please acknowledge the use of ERA5 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 dataset as follows:

Dataset citable as: Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), date of access. https://cds.climate.copernicus.eu/cdsapp#!/home

References

Global reanalysis: goodbye ERA-Interim, hello ERA5.

Global stratospheric temperature bias and other stratospheric aspects of ERA5 and ERA5.1

Further ERA5 references are available from the ECMWF e-Library.