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Introduction
Here we document the
ERA5CAMS reanalysis dataset, which, eventually, will cover the period January
19502003 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
Table 7: stream=mnth/moda/edmm/edmo, levtype=sfc or wamo/wamd/ewmm/ewmo: monthly mean surface and single level and wave parameters: exceptions from Tables 1-6
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 set | Version/Period |
---|---|
MACCity anthropognic emissions | MACCity (trend: ACCMIP + RCP8.5) & CO emission upgrade Stein et al. (2014) |
GFAS | v1.2: 20030101- |
Dry deposition | Sumo dry deposition |
VOC emissions | Monthly mean VOC emissions calculated by the MEGAN model using MERRA reanalysed meteorology (Sindelarova et al., 2014) |
CO2 ocean fluxes | Takahashi et al. (2009) climatology |
CO2 emissions from aviation | Based on ACCMIP NO emissions from aviation scaled to annual total CO2 from EDGAR aviation emissions. |
CO2 ecosystem fluxes bias corrected with BFAS | Based on CHTESSEL (modelled online in C-IFS) |
CO2 anthropogenic emissions | EDGARv4.2FT2010 (2003-2010) |
CH4 wetland emissions | LPJ-HYMN climatology (Spanhi et al., 2011) |
CH4 total emissions | based on EDGARv4.2FT2010 , LPJ-HYMN wetland climatology and other natural sources/sinks (2003-2010) |
CH4 chemical sink | based on Bergamaschi et al. (2009) dataset |
CH4 anthropogenic emissions | EDGARv4.2FT2010 (2003-2010) |
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.
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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:
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:
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
- .
- 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.
- .
- , 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.
- 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
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
* reprocessed dataset
+ when different than the satellite agency
In-situ data, provided by WMO WIS
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
At the time of writing (2017-07) we are aware of these issues with ERA5:
ERA5 shows too strong tropical jet in the mesosphere
ERA5 has poor fit to radiosonde temperatures in the lower stratosphere indicating some cold bias
Although small values of ensemble spread correctly mark more confident estimates than large values, numerical values are over confident
- 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.
This list will be updated as we become aware of further issues in ERA5.
How to cite CAMS Reanalysis
Please acknowledge the use of ERA5 as stated in the Copernicus C3S/CAMS License agreement:
"Where the Licensee communicates to the public or distributes or publishes C3S Information, the Licensee shall inform the recipients of the source of that information by using the following or any similar notice: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: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
ERA5 references are available from the ECMWF e-Library.
Related articles
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