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Introduction

Here we document the

CAMS reanalysis dataset, which, eventually, will cover the period January

2003 to near real time (NRT), though currently only data for the period 2003-2018  have been released. The CAMS reanalysis is the latest global reanalysis data set of atmospheric composition (AC) produced by the Copernicus Atmosphere Monitoring Service, consisting of 3-dimensional time-consistent AC fields, including aerosols, chemical species and greenhouse gases, though GHG fields will only be released in 2019. The data set builds on the experience gained during the production of the earlier MACC reanalysis and CAMS interim reanalysis.

The CAMS reanalysis was produced using 4DVar data assimilation in CY42R1 of ECMWF’s Integrated Forecast System (IFS), with 60 hybrid sigma/pressure (model) levels in the vertical, with the top level at 0.1 the first tranche of data, released in mid-2017, covers the period 2010-2016.ERA5 was produced using 4DVar 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 25 pressure, 16 10 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) 48h 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 analyses00 UTC.

The data are archived in the ECMWF data archive (MARS) and can be retrieved using the ECMWF Public Dataset service via the WebAPI (ECMWF Member State users can access the data using MARS directly, in the usual manner). In the future, the data will be available from the Climate Data Store (CDS).

The IFS model and data assimilation system

The 4DVar data assimilation uses 12 hour assimilation windows from 09 UTC to 21 UTC and 21 UTC to 09 UTC.

The IFS model documentation for CY41R2 is at various model cycles can be found on https://www.ecmwf.int/search/elibrary/part?solrsort=sort_label%20asc&title=part&secondary_title=41r1&f[0]=ts_biblio_year%3A2016.

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

Data organisation

The data can be accessed using the MARS keywords class=ea and expver=0001 (or ‘dataset’ : “era5” for the ECMWF Public Dataset service via the WebAPI). 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

Spatial grid

The ERA5 HRES data has a resolution of 31km, 0.28125 degrees, and the EDA has a resolution of 62km, 0.5625 degrees. The data are available 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 archived on a reduced latitude/longitude grid with a resolution of 0.36 degrees (HRES) and 1.0 degrees (EDA).

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.

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 (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 in the hour ending at the forecast step
• EDA: accumulations are in the 3 hours ending at the forecast step

Mean rate parameters in ERA5 are similar to accumulations except that the quantities are averaged, instead of accumulated, over the period, so the units include "per second".

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.

Monthly means

Most parameters are also available as synoptic monthly means, for each particular time and forecast step, (stream=mnth/wamo/edmm/ewmm) and monthly means of daily means, for the month as a whole (stream=moda/wamd/edmo/ewmo). For the surface and single level parameters, there are some exceptions which are listed in Table 7.

Monthly means for analyses and instantaneous forecasts 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. Monthly means for accumulations and mean rates are created from data with a forecast period falling within the month. For example, 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 data values for accumulations in stream=moda/edmo (monthly means of daily means) have been scaled to give units "per day". Thus, 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. 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. These two data types 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.

Data format

Model level fields are in GRIB2 format. All other fields are in GRIB1, unless otherwise indicated.

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 1-5 below describe the surface and single level parameters (levtype=sfc), Table 6 describes wave parameters, Table 7 describes the monthly mean exceptions for surface and single level and wave parameters and Tables 8-12 describe upper air parameters on various levtypes.

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

count

name

units

shortName

paramId

an

fc

1

Lake cover

(0 - 1)

cl

26

x

x

2

Lake depth

m

dl

228007

x

x

3

Low vegetation cover

(0 - 1)

cvl

27

x

4

High vegetation cover

(0 - 1)

cvh

28

x

5

Type of low vegetation

~

tvl

29

x

6

Type of high vegetation

~

tvh

30

x

7

Soil type

~

slt

43

x

8

Standard deviation of filtered subgrid orography

m

sdfor

74

x

9

Geopotential

m**2 s**-2

z

129

x

x

10

Standard deviation of orography

~

sdor

160

x

11

Anisotropy of sub-gridscale orography

~

isor

161

x

12

Angle of sub-gridscale orography

radians

anor

162

x

13

Slope of sub-gridscale orography

~

slor

163

x

14

Land-sea mask

(0 - 1)

lsm

172

x

x

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

count

name

units

shortName

paramId

an

fc

1

Convective inhibition

J kg**-1

cin

228001

x

2

Friction velocity

m s**-1

zust

228003

x

3

Lake mix-layer temperature

K

lmlt

228008

x

x

4

Lake mix-layer depth

m

lmld

228009

x

x

5

Lake bottom temperature

K

lblt

228010

x

x

6

Lake total layer temperature

K

ltlt

228011

x

x

7

Lake shape factor

dimensionless

lshf

228012

x

x

8

Lake ice temperature

K

lict

228013

x

x

9

Lake ice depth

m

licd

228014

x

x

10

UV visible albedo for direct radiation

(0 - 1)

aluvp

15

x

x

11

Minimum vertical gradient of refractivity inside trapping layer

m**-1

dndzn

228015

x

12

UV visible albedo for diffuse radiation

(0 - 1)

aluvd

16

x

x

13

Mean vertical gradient of refractivity inside trapping layer

m**-1

dndza

228016

x

14

Near IR albedo for direct radiation

(0 - 1)

alnip

17

x

x

15

Duct base height

m

dctb

228017

x

16

Near IR albedo for diffuse radiation

(0 - 1)

alnid

18

x

x

17

Trapping layer base height

m

tplb

228018

x

18

Trapping layer top height

m

tplt

228019

x

19

Cloud base height

m

cbh

228023

x

20

Zero degree level

m

deg0l

228024

x

21

Instantaneous 10 metre wind gust

m s**-1

i10fg

228029

x

22

Sea-ice cover

(0 - 1)

ci

31

x

x

23

Snow albedo

(0 - 1)

asn

32

x

x

24

Snow density

kg m**-3

rsn

33

x

x

25

Sea surface temperature

K

sst

34

x

x

26

Ice temperature layer 1

K

istl1

35

x

x

27

Ice temperature layer 2

K

istl2

36

x

x

28

Ice temperature layer 3

K

istl3

37

x

x

29

Ice temperature layer 4

K

istl4

38

x

x

30

Volumetric soil water layer 1

m**3 m**-3

swvl1

39

x

x

31

Volumetric soil water layer 2

m**3 m**-3

swvl2

40

x

x

32

Volumetric soil water layer 3

m**3 m**-3

swvl3

41

x

x

33

Volumetric soil water layer 4

m**3 m**-3

swvl4

42

x

x

34

Convective available potential energy

J kg**-1

cape

59

x

x

35

Leaf area index, low vegetation

m**2 m**-2

lai_lv

66

x

x

36

Leaf area index, high vegetation

m**2 m**-2

lai_hv

67

x

x

37

Total column cloud liquid water

kg m**-2

tclw

78

x

x

38

Total column cloud ice water

kg m**-2

tciw

79

x

x

39

Total column supercooled liquid water

kg m**-2

tcslw

228088

x

40

Total column rain water

kg m**-2

tcrw

228089

x

x

41

Total column snow water

kg m**-2

tcsw

228090

x

x

42

Neutral wind at 10 m u-component

m s**-1

u10n

228131

x

x

43

Neutral wind at 10 m v-component

m s**-1

v10n

228132

x

x

44

Surface pressure

Pa

sp

134

x

x

45

Total column water

kg m**-2

tcw

136

x

x

46

Total column water vapour

kg m**-2

tcwv

137

x

x

47

Soil temperature level 1

K

stl1

139

x

x

48

Snow depth

m of water equivalent

sd

141

x

x

49

Charnock

~

chnk

148

x

x

50

Mean sea level pressure

Pa

msl

151

x

x

51

Boundary layer height

m

blh

159

x

x

52

Total cloud cover

(0 - 1)

tcc

164

x

x

53

10 metre U wind component

m s**-1

10u

165

x

x

54

10 metre V wind component

m s**-1

10v

166

x

x

55

2 metre temperature

K

2t

167

x

x

56

2 metre dewpoint temperature

K

2d

168

x

x

57

Soil temperature level 2

K

stl2

170

x

x

58

Soil temperature level 3

K

stl3

183

x

x

59

Low cloud cover

(0 - 1)

lcc

186

x

x

60

Medium cloud cover

(0 - 1)

mcc

187

x

x

61

High cloud cover

(0 - 1)

hcc

188

x

x

62

Skin reservoir content

m of water equivalent

src

198

x

x

63

Total column ozone

kg m**-2

tco3

206

x

x

64

Instantaneous large-scale surface precipitation fraction

(0 - 1)

ilspf

228217

x

65

Convective rain rate

kg m**-2 s**-1

crr

228218

x

66

Large scale rain rate

kg m**-2 s**-1

lsrr

228219

x

67

Convective snowfall rate water equivalent

kg m**-2 s**-1

csfr

228220

x

68

Large scale snowfall rate water equivalent

kg m**-2 s**-1

lssfr

228221

x

69

Instantaneous eastward turbulent surface stress

N m**-2

iews

229

x

x

70

Instantaneous northward turbulent surface stress

N m**-2

inss

230

x

x

71

Instantaneous surface sensible heat flux

W m**-2

ishf

231

x

x

72

Instantaneous moisture flux

kg m**-2 s**-1

ie

232

x

x

73

Skin temperature

K

skt

235

x

x

74

Soil temperature level 4

K

stl4

236

x

x

75

Temperature of snow layer

K

tsn

238

x

x

76

Forecast albedo

(0 - 1)

fal

243

x

x

77

Forecast surface roughness

m

fsr

244

x

x

78

Forecast logarithm of surface roughness for heat

~

flsr

245

x

x

79

100 metre U wind component

m s**-1

100u

228246

x

x

80

100 metre V wind component

m s**-1

100v

228247

x

x

81

Precipitation type

code table (4.201)

ptype

260015*

x

82

K index

K

kx

260121*

x

83

Total totals index

K

totalx

260123*

x

*GRIB2 format

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

count

name

units

shortName

paramId

an

fc

1

Large-scale precipitation fraction

s

lspf

50

x

2

Downward UV radiation at the surface

J m**-2

uvb

57

x

3

Boundary layer dissipation

J m**-2

bld

145

x

4

Surface sensible heat flux

J m**-2

sshf

146

x

5

Surface latent heat flux

J m**-2

slhf

147

x

6

Surface solar radiation downwards

J m**-2

ssrd

169

x

7

Surface thermal radiation downwards

J m**-2

strd

175

x

8

Surface net solar radiation

J m**-2

ssr

176

x

9

Surface net thermal radiation

J m**-2

str

177

x

10

Top net solar radiation

J m**-2

tsr

178

x

11

Top net thermal radiation

J m**-2

ttr

179

x

12

Eastward turbulent surface stress

N m**-2 s

ewss

180

x

13

Northward turbulent surface stress

N m**-2 s

nsss

181

x

14

Eastward gravity wave surface stress

N m**-2 s

lgws

195

x

15

Northward gravity wave surface stress

N m**-2 s

mgws

196

x

16

Gravity wave dissipation

J m**-2

gwd

197

x

17

Top net solar radiation, clear sky

J m**-2

tsrc

208

x

18

Top net thermal radiation, clear sky

J m**-2

ttrc

209

x

19

Surface net solar radiation, clear sky

J m**-2

ssrc

210

x

20

Surface net thermal radiation, clear sky

J m**-2

strc

211

x

21

TOA incident solar radiation

J m**-2

tisr

212

x

22

Vertically integrated moisture divergence

kg m**-2

vimd

213

x

23

Total sky direct solar radiation at surface

J m**-2

fdir

228021

x

24

Clear-sky direct solar radiation at surface

J m**-2

cdir

228022

x

25

Surface solar radiation downward clear-sky

J m**-2

ssrdc

228129

x

26

Surface thermal radiation downward clear-sky

J m**-2

strdc

228130

x

27

Surface runoff

m

sro

8

x

28

Sub-surface runoff

m

ssro

9

x

29

Snow evaporation

m of water equivalent

es

44

x

30

Snowmelt

m of water equivalent

smlt

45

x

31

Large-scale precipitation

m

lsp

142

x

32

Convective precipitation

m

cp

143

x

33

Snowfall

m of water equivalent

sf

144

x

34

Evaporation

m of water equivalent

e

182

x

35

Runoff

m

ro

205

x

36

Total precipitation

m

tp

228

x

37

Convective snowfall

m of water equivalent

csf

239

x

38

Large-scale snowfall

m of water equivalent

lsf

240

x

39

Potential evaporation

m

pev

228251

x

The data values for accumulations in stream=moda/edmo (monthly means of daily means) have been scaled to give units "per day". Thus, 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. 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.

Table 4: stream=oper/enda, levtype=sfc: surface and single level parameters: minimum/maximum

count

name

units

shortName

paramId

an

fc

1

10 metre wind gust since previous post-processing

m s**-1

10fg

49

x

2

Maximum temperature at 2 metres since previous post-processing

K

mx2t

201

x

3

Minimum temperature at 2 metres since previous post-processing

K

mn2t

202

x

4

Maximum total precipitation rate since previous post-processing

kg m**-2 s**-1

mxtpr

228226

x

5

Minimum total precipitation rate since previous post-processing

kg m**-2 s**-1

mntpr

228227

x

Table 5: stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc: surface and single level parameters: vertical integrals (not available for type=em/es)

count

name

units

shortName

paramId

an

fc

1

Vertical integral of mass of atmosphere

kg m**-2

vima

162053

x

x

2

Vertical integral of temperature

K kg m**-2

vit

162054

x

x

3

Vertical integral of kinetic energy

J m**-2

vike

162059

x

x

4

Vertical integral of thermal energy

J m**-2

vithe

162060

x

x

5

Vertical integral of potential+internal energy

J m**-2

vipie

162061

x

x

6

Vertical integral of potential+internal+latent energy

J m**-2

vipile

162062

x

x

7

Vertical integral of total energy

J m**-2

vitoe

162063

x

x

8

Vertical integral of energy conversion

W m**-2

viec

162064

x

x

9

Vertical integral of eastward mass flux

kg m**-1 s**-1

vimae

162065

x

x

10

Vertical integral of northward mass flux

kg m**-1 s**-1

viman

162066

x

x

11

Vertical integral of eastward kinetic energy flux

W m**-1

vikee

162067

x

x

12

Vertical integral of northward kinetic energy flux

W m**-1

viken

162068

x

x

13

Vertical integral of eastward heat flux

W m**-1

vithee

162069

x

x

14

Vertical integral of northward heat flux

W m**-1

vithen

162070

x

x

15

Vertical integral of eastward water vapour flux

kg m**-1 s**-1

viwve

162071

x

x

16

Vertical integral of northward water vapour flux

kg m**-1 s**-1

viwvn

162072

x

x

17

Vertical integral of eastward geopotential flux

W m**-1

vige

162073

x

x

18

Vertical integral of northward geopotential flux

W m**-1

vign

162074

x

x

19

Vertical integral of eastward total energy flux

W m**-1

vitoee

162075

x

x

20

Vertical integral of northward total energy flux

W m**-1

vitoen

162076

x

x

21

Vertical integral of eastward ozone flux

kg m**-1 s**-1

vioze

162077

x

x

22

Vertical integral of northward ozone flux

kg m**-1 s**-1

viozn

162078

x

x

23

Vertical integral of divergence of cloud liquid water flux

kg m**-2 s**-1

vilwd

162079

x

x

24

Vertical integral of divergence of cloud frozen water flux

kg m**-2 s**-1

viiwd

162080

x

x

25

Vertical integral of divergence of mass flux

kg m**-2 s**-1

vimad

162081

x

x

26

Vertical integral of divergence of kinetic energy flux

W m**-2

viked

162082

x

x

27

Vertical integral of divergence of thermal energy flux

W m**-2

vithed

162083

x

x

28

Vertical integral of divergence of moisture flux

kg m**-2 s**-1

viwvd

162084

x

x

29

Vertical integral of divergence of geopotential flux

W m**-2

vigd

162085

x

x

30

Vertical integral of divergence of total energy flux

W m**-2

vitoed

162086

x

x

31

Vertical integral of divergence of ozone flux

kg m**-2 s**-1

viozd

162087

x

x

32

Vertical integral of eastward cloud liquid water flux

kg m**-1 s**-1

vilwe

162088

x

x

33

Vertical integral of northward cloud liquid water flux

kg m**-1 s**-1

vilwn

162089

x

x

34

Vertical integral of eastward cloud frozen water flux

kg m**-1 s**-1

viiwe

162090

x

x

35

Vertical integral of northward cloud frozen water flux

kg m**-1 s**-1

viiwn

162091

x

x

36

Vertical integral of mass tendency

kg m**-2 s**-1

vimat

162092

x

Table 6: stream=wave/ewda/wamo/wamd/ewmm/ewmo: wave parameters

count

name

units

shortName

paramId

an

fc

1

Significant wave height of first swell partition

m

swh1

140121

x

x

2

Mean wave direction of first swell partition

degrees

mwd1

140122

x

x

3

Mean wave period of first swell partition

s

mwp1

140123

x

x

4

Significant wave height of second swell partition

m

swh2

140124

x

x

5

Mean wave direction of second swell partition

degrees

mwd2

140125

x

x

6

Mean wave period of second swell partition

s

mwp2

140126

x

x

7

Significant wave height of third swell partition

m

swh3

140127

x

x

8

Mean wave direction of third swell partition

degrees

mwd3

140128

x

x

9

Mean wave period of third swell partition

s

mwp3

140129

x

x

10

Wave Spectral Skewness

dimensionless

wss

140207

x

x

11

Free convective velocity over the oceans

m s**-1

wstar

140208

x

x

12

Air density over the oceans

kg m**-3

rhoao

140209

x

x

13

Normalized energy flux into waves

dimensionless

phiaw

140211

x

x

14

Normalized energy flux into ocean

dimensionless

phioc

140212

x

x

15

Normalized stress into ocean

dimensionless

tauoc

140214

x

x

16

U-component stokes drift

m s**-1

ust

140215

x

x

17

V-component stokes drift

m s**-1

vst

140216

x

x

18

Period corresponding to maximum individual wave height

s

tmax

140217

x

x

19

Maximum individual wave height

m

hmax

140218

x

x

20

Model bathymetry

m

wmb

140219

x

x

21

Mean wave period based on first moment

s

mp1

140220

x

x

22

Mean wave period based on second moment

s

mp2

140221

x

x

23

Wave spectral directional width

dimensionless

wdw

140222

x

x

24

Mean wave period based on first moment for wind waves

s

p1ww

140223

x

x

25

Mean wave period based on second moment for wind waves

s

p2ww

140224

x

x

26

Wave spectral directional width for wind waves

dimensionless

dwww

140225

x

x

27

Mean wave period based on first moment for swell

s

p1ps

140226

x

x

28

Mean wave period based on second moment for swell

s

p2ps

140227

x

x

29

Wave spectral directional width for swell

dimensionless

dwps

140228

x

x

30

Significant height of combined wind waves and swell

m

swh

140229

x

x

31

Mean wave direction

degrees

mwd

140230

x

x

32

Peak period of 1D spectra

s

pp1d

140231

x

x

33

Mean wave period

s

mwp

140232

x

x

34

Coefficient of drag with waves

dimensionless

cdww

140233

x

x

35

Significant height of wind waves

m

shww

140234

x

x

36

Mean direction of wind waves

degrees

mdww

140235

x

x

37

Mean period of wind waves

s

mpww

140236

x

x

38

Significant height of total swell

m

shts

140237

x

x

39

Mean direction of total swell

degrees

mdts

140238

x

x

40

Mean period of total swell

s

mpts

140239

x

x

41

Mean square slope of waves

dimensionless

msqs

140244

x

x

42

10 metre wind speed

m s**-1

wind

140245

x

x

43

Altimeter wave height

m

awh

140246

x

44

Altimeter corrected wave height

m

acwh

140247

x

45

Altimeter range relative correction

~

arrc

140248

x

46

10 metre wind direction

degrees

dwi

140249

x

x

47

Wave spectral kurtosis

dimensionless

wsk

140252

x

x

48

Benjamin-Feir index

dimensionless

bfi

140253

x

x

49

Wave spectral peakedness

dimensionless

wsp

140254

x

x

50

2D wave spectra (single)

m**2 s radian**-1

2dfd

140251*

x

*for 30 frequencies and 24 directions

count

name

units

shortName

paramId

an

fc

1

UV visible albedo for direct radiation

(0 - 1)

aluvp

15

x

no mean

2

UV visible albedo for diffuse radiation

(0 - 1)

aluvd

16

x

no mean

3

Near IR albedo for direct radiation

(0 - 1)

alnip

17

x

no mean

4

Near IR albedo for diffuse radiation

(0 - 1)

alnid

18

x

no mean

5

Magnitude of turbulent surface stress

N m**-2 s

magss

48

x

6

10 metre wind gust since previous post-processing

m s**-1

10fg

49

no mean

7

Maximum temperature at 2 metres since previous post-processing

K

mx2t

201

no mean

8

Minimum temperature at 2 metres since previous post-processing

K

mn2t

202

no mean

9

10 metre wind speed

m s**-1

10si

207

x

x

10

Maximum total precipitation rate since previous post-processing

kg m**-2 s**-1

mxtpr

228226

no mean

11

Minimum total precipitation rate since previous post-processing

kg m**-2 s**-1

mntpr

228227

no mean

12

Altimeter wave height

m

awh

140246

no mean

13

Altimeter corrected wave height

m

acwh

140247

no mean

14

Altimeter range relative correction

~

arrc

140248

no mean

15

2D wave spectra (single)

m**2 s radian**-1

2dfd

140251

no mean

Table 8: stream=oper/enda/mnth/moda/edmm/edmo, levtype=pl: pressure level parameters: instantaneous

count

name

units

shortName

paramId

an

fc

1

Potential vorticity

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

pv

60

x

x

2

Specific rain water content

kg kg**-1

crwc

75

x

x

3

Specific snow water content

kg kg**-1

cswc

76

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

Divergence

s**-1

d

155

x

x

12

Relative humidity

%

r

157

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

Table 9: 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 10: 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 11: 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 12: stream=oper/enda/mnth/moda/edmm/edmo, levtype=ml: model level parameters: mean rates

en/forecasts/documentation-and-support/changes-ecmwf-model/ifs-documentation. The model used in the CAMS reanalysis includes several updates to the aerosol and chemistry modules on top of the standard CY42R1 release, which are listed below. Please note that 42r1 documentation is not available on the page, but the code for the earlier and later cycles is available for reference.

Aerosol model

• Updated aerosol optical properties, especially for organic matter ( Bozzo et al., 2017).
• Bug fixes to sedimentation, which was unreasonably weak for some dust and sea-salt bins, with corresponding re-tuning of sea-salt scavenging.
• SO₂ dry deposition velocities updated to match those used in the chemistry scheme (from SUMO).
• New parametrisation of anthropogenic Secondary Organic Aerosol (SOA) production, proportional to non-biomass-burning CO emissions.
• More detailed SO₂ to sulfate aerosol conversion with dependence on temperature and relative humidity, and overall decrease in the conversion timescale especially at high latitudes.
• Increased sulfate dry deposition velocity over ocean.
• Mass fixer extended to aerosol species.
• Scaling of biomass-burning Black Carbon (BC) emissions using the ratio of BC AOD (CAMS interim reanalysis) / BC AOD (CAMS interim control run).
• 80% of SO₂ emissions are released in the two lowest model levels (as an update of tendencies) rather than at surface (fluxes)

Chemistry mechanism

The chemical mechanism of the IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in CTM Transport Model 5 (TM5). In the CAMS reanalysis the model as documented in Flemming et al. (2015) and Flemming et al. (2017) is used with the following updates:

• Update of heterogeneous rate coefficients for N2O5 and HO2 based on clouds and aerosol
• Modification of photolysis rates by aerosol
• Dynamic tropopause definition based on T profile for coupling to stratosphere and tropospheric mass diagnostics
• Monthly mean VOC emissions calculated by the MEGAN model using MERRA reanalysed meteorology (Sindelarova et al., 2014) for all VOCs and for whole period 2003-2015 period.
• Bugfixes, in particular for diurnal cycle of dry deposition whose correction has decreased ozone dry deposition (about 15-20%)     
• The version number for the chemistry scheme is CHEM_VER=15

Greenhouse Gases

The model configuration for greenhouse gases is based on the specification of the following components documented in the listed papers below:

• Emissions for CO2 are documented in Agusti-Panareda et al. (2014), Massart et al. (2016).
• Bias correction for CO2 ecosystem fluxes based on the Biogenic Flux Adjustment Scheme is documented by Agusti-Panareda et al. (2016)
• Emissions and loss rate for CH4 is documented in Massart et al. (2014)
• Mass fixer configuration for CO2 and CH4 is documented by Agusti-Panareda et al. (2017)

Emission datasets

The emissions datasets used to produce the CAMS reanalysis are listed in Table 1. They include the MACCity anthropogenic emission, GFAS fire emissions, MEGAN biogenic emissions and several GHG emission datasets.

Table 1: Emission datasets used in the CAMS reanalysis

Data organisation and access

The data is listed in ECMWF's public data catalogue. To access the data use the ECMWF Web API with ‘dataset’:'eac4'.

Users with access to MARS can also browse the data on the MARS catalogue under class=mc and expver=eac4.

Stream:

• oper: sub-daily
• mnth: synoptic monthly means
• moda:monthly means of daily means

Type:

• an: analyses
• fc: forecasts

Levtype:

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

Spatial grid

The CAMS reanalysis data have a resolution of approximately 80 km. The data are available either as spectral coefficients with a triangular truncation of T255 or on a reduced Gaussian grid with a resolution of N128. These grids are so called "linear grids", sometimes referred to as TL255.

Temporal frequency

For sub-daily data for the CAMS reanalysis (stream=oper) the analyses (type=an) are available 3-hourly. The daily forecast, run from 00 UTC, has 3-hourly steps from 0 to 48 hours for the 3D model level and pressure level fields, and hourly steps from 0 to 48 hours for the surface fields.

Monthly means

Several parameters are also available as synoptic monthly means, for each particular time and forecast step (stream=mnth) and as monthly means of daily means, for the month as a whole (stream=moda).

Monthly means for analyses and instantaneous forecasts 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. Monthly means for accumulations and mean rates are created from data with a forecast period falling within the month. For example, 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.

Data format

Model level fields are in GRIB2 format. All other fields are in GRIB1, unless otherwise indicated.

Level listings

Pressure levels: 1000/950/925/900/850/800/700/600/500/400/300/250/200/150/100/70/50/30/20/10/7/5/3/2/1

Potential temperature levels: 300/315/320/330/350/370/395/475/600/850

Potential vorticity level: 2000

Model levels: 1/to/60, which are described at https://www.ecmwf.int/en/forecasts/documentation-and-support/60-model-levels.

Parameter listings 

The archive of available parameters can be browsed here.

Satellite Data

The atmospheric composition satellite retrievalsused as input into the CAMS reanalysis are listed below. The following abbreviations are used in Table 1. TC: Total column, TRC: Tropospheric column, PROF: profiles, PC: Partial columns, ColAv: Column average mixing ratio, QR= quality flag given by data providers, SOE: Solar elevation, MODORO: Model orography, PRESS_RL= pressure at bottom of layer, LAT: Latitude.

Validation reports

Validation Reports for the CAMS reanalysis can be found on the CAMS Quality Assurance website.

Guidelines

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

• Users who want to use meteorological data only are advised to use the ERA5 meteorological reanalysis.
• CAMS data users please use the 'GEMS Ozone' (param 210203) and 'Total Column GEMS Ozone' (param 210206) fields. These are produced specifically for CAMS using the full tropospheric chemistry scheme, see also CAMS Global data: What is "GEMS ozone".

Known issues

At the time of writing (2017-11) we are aware of these issues with the CAMS reanalysis:

• Validation of AOD with Aeronet data has show there are some hot spots around outgassing volcanoes (in particular Mauna Loa and Mexico City) with high analysis AOD values that degrade the global average RMSE. If calculating global mean statistics it is advisable to exclude those two stations as unrepresentative. This is a side effect of model-resolution orography not resolving the height of the volcanoes that has been unmasked by recent enhancements to the SO2 oxidation scheme which improve aerosol on the global scale.
• During 2003 the ozone analysis has a degraded quality (bigger biases with respect to observations) in Arctic and Antarctic free troposphere because MIPAS and SCIAMACHY data of lower quality were assimilated.
• Between March-August 2004 no ozone profile data were available for assimilation. This affects the vertical structure of the ozone analysis and we see larger biases wrt ozone sondes, especially in the Antarctic.
• From 2013 onwards there is a larger seasonally varying bias in ozone in the free troposphere, particularly in the Arctic and Antarctic that is not seen in the control run. The reason for this bias is a change in the observing system, namely the change from 13-layer SBUV/2 data to 21-layer SBUV/2 data in July 2013 (see Table 2) that unfortunately has an impact on tropospheric ozone. A similar bias is seen in the NRT CAMS ozone analysis which also uses the 21-layer SBUV/2 data after 2013.
• During 2003 the seasonal cycle of the tropospheric column NO2 is not well represented because of the assimilation of SCIAMACHY NO2 data of degraded quality.

• The use of the NOx variable from the CAMS reanalysis (as well as from the CAMS interim re-analysis and the CAMS operational system) is not recommended. The user is advised to download NO and NO2 separately and to add them up. Please note that a conversion of the mass mixing ratios [kg/kg] to volume mixing rations / molar fractions [mol/mol] is needed to do this in a meaningful way.

This list will be updated as we become aware of further issues in the CAMS reanalysis.

How to cite the CAMS Reanalysis

Please acknowledge the use of the CAMS reanalysis as stated in the Copernicus C3S/CAMS License agreement:

• "Where the Licensee communicates to the public or distributes or publishes CAMS Information, the Licensee shall inform the recipients of the source of that information by using the following or any similar notice:

  'Generated using Copernicus Atmosphere Monitoring Service Information [Year]'.

• Where the Licensee makes or contributes to a publication or distribution containing adapted or modified CAMS Information, the Licensee shall provide the following or any similar notice:

  'Contains modified Copernicus Atmosphere Monitoring Service Information [Year]';

Any such publication or distribution shall state that "neither the European Commission nor ECMWF is responsible for any use that may be made of the information it contains."

References

• Agustí-Panareda, A., and Coauthors, 2014: Forecasting global atmospheric CO₂, Atmos. Chem. Phys., 14, 11959-11983, https://doi.org/10.5194/acp-14-11959-2014.
• Agusti-Panareda, A, S. Massart, F. Chevallier, G. Balsamo, S. Boussetta, E. Dutra, and A. Beljaars, 2016: A biogenic CO2 flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO2 analyses and forecasts, Atmos. Chem. Phys., 16, 10399–10418, https://doi.org/10.5194/acp-16-10399-2016.
• Agusti-Panareda, A., M. Diamantakis, V. Bayona, F. Klappenbach, and A. Butz, 2017: Improving the inter-hemispheric gradient of total column atmospheric CO₂ and CH₄ in simulations with the ECMWF semi-Lagrangian atmospheric global model, Geosci. Model Dev., 10, 1-18,  https://doi.org/10.5194/gmd-10-1-2017.
• Bergamaschi, P., and Coauthors, 2009: Inverse modeling of global and regional CH₄ emissions using SCIAMACHY satellite retrievals, J. Geophys. Res., 114, D22301, https://doi.org/10.1029/2009JD012287.
• Bozzo, A., S. Remy, A. Benedetti, J.Flemming, P. Bechtold, M.J. Rodwell, and J.-J. Morcrette, 2017: Implementation of a CAMS-based aerosol climatology in the IFSA. ECMWF Technical Memorandum 801, 33 pp, https://www.ecmwf.int/sites/default/files/elibrary/2017/17219-implementation-cams-based-aerosol-climatology-ifs.pdf
  
• Flemming, J., and Coauthors, 2015: Tropospheric chemistry in the Integrated Forecasting System of ECMWF. Geosci. Model Dev., 8, 975–1003, https://doi.org/10.5194/gmd-8-975-2015.
• Flemming, J., and Coauthors, 2017: The CAMS interim Reanalysis of Carbon Monoxide,Ozone and Aerosol for 2003–2015. Atmos. Chem. Phys., 17, 1945–1983, https://doi.org/10.5194/acp-17-1945-2017.
• Massart, S., A. Agusti-Panareda, I. Aben, A. Butz, F. Chevallier, C. Crevoisier, R. Engelen, C. Frankenberg, and O. Hasekamp, 2014:  Assimilation of atmospheric methane products into the MACC-II system: from SCIAMACHY to TANSO and IASI, Atmos. Chem. Phys., 14, 6139-6158, https://doi.org/10.5194/acp-14-6139-2014
  
• Massart, S., and Coauthors, 2016: Ability of the 4-D-Var analysis of the GOSAT BESD XCO₂ retrievals to characterize atmospheric CO₂ at large and synoptic scales, Atmos. Chem. Phys., 16, 1653-1671,https://doi.org/10.5194/acp-16-1653-2016.
• Spahni, R., and Coauthors, 2011: Constraining global methane emissions and uptake by ecosystems. Biogeosciences, 8, 1643–1665, https://doi.org/10.5194/bg-8-1643-2011.
  
• Stein, O., M. G. Schultz, I. Bouarar2, H. Clark, V. Huijnen, A. Gaudel, M. George, and C. Clerbaux, 2014: On the wintertime low bias of Northern Hemisphere carbon monoxide found in global model simulations. Atmos. Chem. Phys., 14, 9295–9316, https://doi.org/10.5194/acp-14-9295-2014.
• Takahashi, T., and Coauthors, 2009: Climatological mean and decadal change in surface ocean pCO2, and netsea–air CO2flux over the global oceans. Deep-Sea Research II, 56, 554–577, https://doi.org/10.1016/j.dsr2.2008.12.009.

A reference paper is available from www.atmos-chem-phys.net/19/3515/2019/ and further CAMS reanalysis references will be available from the ECMWF e-Library in the future. 

An ECMWF newsletter article 'The new CAMS global reanalysis of atmospheric composition' is available from: https://www.ecmwf.int/node/18821

Mailing list

To be kept informed of the latest news associated to the CAMS Reanalysis products, you may subscribe to the CAMS Global Reanalysis mailing list.

Observations

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

Satellite Data