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Introduction
This user guide describes the datasets released from the Arctic Regional Reanalysis service, which is part of the Copernicus Climate Change Service (C3S). The datasets will include the actual grid point reanalysis information on different levels (atmospheric vertical levels, surface including soil). This version also provides details on the uncertainty information provided. We will refer to the dataset as the CARRA (Copernicus Arctic Regional ReAnalysis) dataset.
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Table 1: Overview of single level variables. Some variables have not yet been uploaded to CDS, these are marked with * and unfortunately are not included amongst the released reanalysis data. Most static fields (except land-sea mask and orography) marked with * * are available only as NetCDF-files below. Anchor table1 table1
Precipitation, cloud water and humidity | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
2r | % | 260242 | yes | yes | 2m | |
2sh | kg/kg | 174096 | yes | yes | 2m | |
tciwv | kg/m2 | 260057 | yes | yes | vertically integrated above the surface | |
tclw | kg/m2 | 78 | no | yes | vertically integrated above the surface | |
tciw | kg/m2 | 79 | no | yes | vertically integrated above the surface | |
tcolg | kg/m2 | 260001 | yes | yes | vertically integrated above the surface | |
tp | kg/m2 | 228228 | no | yes | surface | |
tirf | kg/m2 | 235015 | no | yes | surface | |
titspf | kg/m2 | 260645 | no | yes | surface | |
ptype | integer code | 260015 | no | yes | surface | |
sro | kg/m2 | 174008 | no | yes | surface | |
Percolation (drainage) | perc | kg/m2 | 260430 | no | yes | sub-surface |
Temperature and wind speed | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
10si | m/s | 207 | yes | yes | 10m | |
10wdir | degrees | 260260 | yes | yes | 10m | |
10m u-component of wind (defined relative to the rotated model grid) | 10u | m/s | 165 | yes | yes | 10m |
10m v component of wind | 10v | m/s | 166 | yes | yes | 10m |
10m eastward wind gust since previous post-processing | 10efg | m/s | 260646 | no | yes | 10m |
10m northward wind gust since previous post-processing | 10nfg | m/s | 260647 | no | yes | 10m |
10fg | m/s | 49 | no | yes | 10m | |
mx2t | K | 201 | no | yes | 2m | |
mn2t | K | 202 | no | yes | 2m | |
2t | K | 167 | yes | yes | 2m | |
skt | K | 235 | yes | yes | Surface |
Accumulated fluxes | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
al | % | 260509 |
yes** | yes | surface | ||||
eva | kg/m2 | 260259 | no | yes | surface | |
tisef | kg/m2 | 235072 | no | yes | surface | |
sshf | J/m2 | 146 | no | yes | surface | |
slhf | J/m2 | 147 | no | yes | surface | |
tislhef | J/m2 | 235019 | no | yes | surface | |
tislhsf | J/m2 | 235071 | no | yes | surface | |
dsrp | J/m2 | 47 | no | yes | surface | |
tidirswrf | J/m2 | 260264 | no | yes | surface | |
ssr | J/m2 | 176 | no | yes | surface | |
ssrd | J/m2 | 169 | no | yes | surface | |
ssrc | J/m2 | 210 | no | yes | surface | |
str | J/m2 | 177 | no | yes | surface | |
strd | J/m2 | 175 | no | yes | surface | |
strc | J/m2 | 211 | no | yes | surface | |
Top net solar radiation | tsr | J/m2 | 178 | no | yes | surface |
ttr | J/m2 | 179 | no | yes | surface | |
tisemf | kg⋅m/s | 235017 | no | yes | surface | |
tisnmf | kg⋅m/s | 235018 | no | yes | surface | |
Pressure | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
msl | Pa | 151 | yes | yes | surface (scaled to sea level) | |
sp | Pa | 134 | yes | yes | surface | |
Geometric cloud properties | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
hcc | % | 3075 | yes | yes | above 5000m | |
mcc | % | 3074 | yes | yes | 2500m - 5000m | |
lcc | % | 3073 | yes | yes | surface - 2500m | |
tcc | % | 228164 | yes | yes | above ground | |
fog | % | 260648 | no | yes | lowest model level | |
vis | m | 3020 | yes | yes | lowest model level | |
cdcb | m | 260107 | yes | yes | - | |
cdct | m | 260108 | yes | yes | - | |
Snow | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
rsn | kg/m3 | 33 | yes | yes | surface | |
sd | kg/m2 | 228141 | yes | yes | surface | |
fscov | 0-1 | 260289 | yes | no | surface | |
asn | % | 228032 | yes | no | surface | |
Surface roughness lengths | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
sr | m | 173 | yes | no | surface | |
srlh | m | 260651 | yes | no | surface | |
Sea states | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
sst | K | 34 | yes | no | surface | |
ci | 0-1 | 31 | yes | no | surface | |
sist | K | 260649 | yes | yes | surface | |
sithick | m | 174098 | yes | no | surface | |
sitd | m | 260650 | yes | yes | surface | |
Static fields | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
lsm | % | 172 | no | no | surface | |
Sea tile fraction |
* | NA | 0-1 | NA | no | no | surface |
Inland water tile fraction |
* | NA | 0-1 | NA | no | no | surface |
Urban tile fraction* |
NA | 0-1 | NA | no | no | surface | |
Nature tile fraction* |
NA | 0-1 | NA | no | no | surface | |
Glacier fraction* | NA | 0-1 | NA | no | no | surface |
Subgrid orography average slope* | NA | 0-1 | NA | no | no | surface |
Subgrid orography standard deviation* | NA | m | NA | no | no | surface |
orog | m | 228002 | no | no | surface |
The static fields marked as * * above are available as NetCDF files for the West and East domain respectively here: fractions.west.nc and fractions.east.nc
** Albedo is available at analysis time, but as a static climatological value which we discourage for use. Only the forecast time albedos should be used, see end of Section 5.5 below.
Soil level variables
Soil level variables are given for two model depths, where the first depth is the soil surface and the second depth is the so-called root depth. The root depth varies with the cover type climatology. Please note that the soil level variables are accommodated in the Arctic Regional Reanalysis single level variables catalogue entry.
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Soil level variables | |||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… |
vsi | m³/m³ | 260644 | yes | yes | |
vsw | m³/m³ | 260199 | yes | yes |
Model level variables
Model level variables are output at 65 hybrid model levels of the HARMONIE-AROME model. These follow the surface at the lowest levels and are gradually evolved into pure pressure levels at the highest levels. These are the levels at which the model computations are done. The height level and pressure level variables are interpolated from these data.
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Table 3: Overview of model level variables Anchor table3 table3
Model level variables | |||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2 |
q | kg/kg | 133 | yes | yes | |
t | K | 130 | yes | yes | |
u-component of wind (defined relative to the rotated model grid) | u | m/s | 131 | yes | yes |
v-component of wind (defined relative to the rotated model grid) | v | m/s | 132 | yes | yes |
ccl | % | 260257 | yes | yes | |
clwc | kg/kg | 246 | yes | yes | |
ciwc | kg/kg | 247 | yes | yes | |
crwc | kg/kg | 75 | yes | yes | |
cswc | kg/kg | 76 | yes | yes | |
grle | kg/kg | 260028 | yes | yes | |
tke | J/kg | 260155 | yes | yes |
Pressure level variables
Pressure level variables are interpolated to 23 specific pressure levels: 1000, 950, 925, 875, 850, 800, 750, 700, 600, 500, 400, 300, 200, 100, 70, 50, 30, 20 and 10 hPa. Thus, they are on isobaric surfaces.
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Pressure level variables | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | |
r | % | 157 | yes | yes | ||
t | K | 130 | yes | yes | ||
u-component of wind (defined relative to the rotated model grid) | u | m/s | 131 | yes | yes | |
v-component of wind (Component defined relative to the rotated model grid) | v | m/s | 132 | yes | yes | |
wz | m/s | 260238 | yes | yes | ||
ccl | % | 260257 | yes | yes | ||
clwc | kg/kg | 246 | yes | yes | ||
ciwc | kg/kg | 247 | yes | yes | ||
crwc | kg/kg | 75 | yes | yes | ||
cswc | kg/kg | 76 | yes | yes | ||
grle | kg/kg | 260028 | yes | yes | ||
papt | K | 3014 | yes | yes | ||
z | m²/s² | 129 | yes | yes | ||
pv | K·m²/ (kg·s) | 60 | yes | yes |
Height level variables
Height level variables are interpolated to 11 specific height levels: 15, 30, 50, 75, 100, 150, 200, 250, 300, 400 and 500 metres above the surface.
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Height level variables | |||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… |
r | % | 157 | yes | yes | |
t | K | 130 | yes | yes | |
ws | m/s | 10 | yes | yes | |
wdir | deg | 3031 | yes | yes | |
clwc | kg/kg | 246 | yes | yes | |
ciwc | kg/kg | 247 | yes | yes | |
Pressure | pres | Pa | 54 | yes | yes |
Details about the data fields
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The wind direction D clockwise from North can be calculated as
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LaTeX Formatting |
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$$ D = tan_atan {2}^{-1} \frac({u/U},{v/V}) + 180^{\circ} + \alpha, (4) $$ |
where 𝛼 where 𝛼 is the local rotation of the model grid relative to North, and tan2-1 atan2 is the very specific 2-argument arcus tangens function atan2, which is included in most programming languages. With atan2 both the sign in the numerator and the denominator are independently important for the resulting angle. Take For definition of the atan2 function, see for instance at https://en.wikipedia.org/wiki/Atan2. Take care to check if the atan2 result is in radians, in which case it should be converted to degrees with the factor 180°/π. Also take care to check if the resulting direction is between 0° and 360°. Note that the wind direction is the direction from which the wind comes! The grid rotation angle 𝛼 can be computed with this script: https://github.com/metno/NWPdocs/wiki/From/Examples/#wind-direction-obtained-from-x-y-wind-to-wind-direction.
10-metre u and v wind gust components are also output. These are computed from the diagnosed 10-metre winds and the turbulent kinetic energy (pers. comm. Gwenaëlle Hello, Meteo France, 2007).
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All energy fluxes at the surface are output as accumulated variables from the initial time of the forecast to the forecast hour in question with the unit J/m2. They . Note that a different accumulation applies to the albedo, see below. The other accumulated variables are considered positive downward to the surface. Energy fluxes are not output variables at the analysis times. Average hourly energy fluxes in W/m2 can be computed by subtracting two successive hourly accumulated variables and dividing by 3600 s. The solar radiation variables at the surface are accumulated downward, direct, direct normal and net solar radiation. Direct normal solar radiation is considered on a plane perpendicular to the direction to the sun, while the other solar variables are considered on a horizontal surface. The albedo in units of % is also given. Multiplying this with the accumulated downward solar radiation gives the accumulated upward solar radiation. The net solar radiation is the difference between the downward solar radiation and the upward solar radiation. Note that the albedo should only be used from forecast data, as the analysis time albedo are is incorrect – and not used in the model. The variable accumulated net clear sky solar radiation is the net solar radiation of a cloud free atmosphere. Dividing this with one minus the albedo gives the accumulated downward clear sky solar radiation. The thermal radiance variables at the surface are accumulated downward, net, and net clear sky thermal radiation. The thermal radiation variables are all considered on a horizontal surface. The net thermal radiation is the difference between the downward thermal radiation and the upward thermal radiation. The upward thermal radiation can be calculated by subtracting the net thermal radiation from the downward thermal radiation. The accumulated surface sensible heat flux is the conductive energy from the atmosphere to the surface. If this is going from the surface to the atmosphere it has negative values. The accumulated latent heat flux is the sum of all latent energy fluxes that are due to the phase transitions of water. Here condensation causes a positive latent heat flux to the surface, and evaporation causes a negative heat flux from the surface. The latent heat due to evaporation and sublimation are given as individual output variables.
The u and v components of the accumulated surface momentum flux are given as output variables in units of kg m/s. The momentum roughness length and the heat roughness length as used in the model are given as output in units of m. Note that the roughness lengths should only be used from forecast data, as the analysis time values are incorrect – and not used in the model.
Variables at the top of the atmosphere
The albedo is accumulated with a special procedure, noting that it changes over time depending on e.g. snowfall. It is derived from the formula: albedo = 1 - SWnet/SW↓, where SW↓ is the downward solar flux at the surface, and SWnet is the net (downward minus upward) solar flux at the surface. The solar fluxes are accumulated over a given time interval. This time interval is one hour until the +6h forecast range and three hours afterwards. So these albedos represent averages over hourly or 3-hourly periods prior to the forecast time. Instantaneous albedos at the output times would be less precise than using these accumulated variables, see alsosection 4 in the note by Hogan, 2015. The problem with this procedure is that in some cases unphysical albedo values (>100%) may occur due to rounding errors. There is also an analysis time albedo provided in the data set, which can be quite different from the actual albedo at forecast times ad therefore it is not recommended to be used.
Variables at the top of the atmosphere
At the top of the atmosphere (TOA) the accumulated solar net TOA radiation and the accumulated thermal net TOA radiation are output variables in At the top of the atmosphere (TOA) the accumulated solar net TOA radiation and the accumulated thermal net TOA radiation are output variables in units of J/m2. These are both considered on a horizontal surface and are both positive in the downward direction. Since the downward solar TOA radiation is always larger than the upward solar TOA radiation, the solar net TOA radiation is always positive. Since there is virtually no downward thermal TOA radiation, the thermal net TOA radiation is always negative. The TOA is the highest model half-level. Thus, the variables at this level are explicitly calculated.
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The snow variables are given as instantaneous values from the most recent model time step relative to the output time. The snow density output unit is kg/m3, the snow water equivalent (SWE) output is in units of kg/m2, and the snow fraction output has fractional units in the range 0-1. The snow depth can be derived from these variables.
Sea and sea
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ice variables
For the sea the sea surface temperature is is output in units of K. For areas partially or completely covered with sea - ice, the following variables are output: Sea - ice area fraction [-], upper layer sea ice temperature [K], sea - ice thickness [m], and sea - ice snow thickness [m]. Here the sea-. For sea ice thickness please note that the routine that computes this variable does not reproduce the evolution of ice thickness with all its complexity. Rather this variable should be treated as a rough estimate in order to get reasonable estimations for the energy fluxes. The sea ice fraction and sea surface temperatures are in fact interpolated input data and are only updated once every day. During the course of a forecast they are kept constant. All other sea and sea - ice variables are given as instantaneous values from the most recent model time step relative to the output time.
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The model level variables are computed at the full model levels, and are given as instantaneous values from the most recent model time step relative to the output time. There are 65 vertical model levels in HARMONIE-AROME. These full model levels are hybrid-sigma coordinates that are counted from the model top toward the surface. They go from being pure pressure levels, i.e. levels with constant pressure starting at 10 hPa, 30 hPa, etc. to being relative to the surface topography in height. Level 64 is at approximately 30 m height and level 65 is at approximately 12 m height above the surface. For a more detailed description of the vertical model layers, see Annex 8.3. The following thermodynamic variables are the output variables at model levels: Temperature [K], u-component of wind [m/s], v-component of wind [m/s], turbulent kinetic energy [J/kg]. Here turbulent kinetic energy is the mean kinetic energy per unit mass from eddies in turbulent flow. Note that the HARMONIE-AROME weather forecasting model with 2.5 x 2.5 km2 resolution does not explicitly resolve this turbulent energy. The u- and v- wind components follow the direction of the Lambertian model grid with the u-component being directed 90 degrees clockwise relative to the v-component. From these model level wind components, the model level wind speed and wind direction relative north can be calculated with Equations 3 and 4. The grid rotation angle 𝛼 can be computed with this script: https://github.com/metno/NWPdocs/wiki/From-x-y-wind-to-wind-direction.
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Static fields are output variables that do not change depending on the model initial time or the forecast length (in other words they are time-independent). These include the land-sea mask, that is the fraction of land in a given model grid box of 2.5 x 2.5 km2 in units of %, and the orography in units of m. There are two more orography-related static parameters: subgrid orography average slope and subgrid orography standard deviation. For each model grid box in HARMONIE-AROME 4 tile fractions are defined in units of fraction. These are: The fraction of sea, the fraction of inland water (lakes and rivers), the fraction of urban areas, and the fraction of nature, i.e. land areas that are not inland water or urban. The fraction of glaciers is also output. This is assumed to be a constant field with glacier extents representative of the middle of the full reanalysis period (19971991-2021). Glacier extent in remote Arctic locations is not available as accurately mapped yearly datasets. The official maps are outdated due to major calving events in the recent decades. HARMONIE-AROME has not yet been designed to deal with changing land-sea masks or other surface classifications. Thus, these are static fields.
What are the uncertainties of the data fields?
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It should be noted that some reanalysis systems aim at describing how reanalysis uncertainties depend on the weather situation, and for instance in ERA5 this has been done by using a so-called ensemble data assimilation system. (For a description of ensemble data assimilation, see for instance the report on the system developed by ECMWF, https://www.ecmwf.int/en/elibrary/7496910125-ensemble-data-assimilations-ecmwf .) Unlike ERA5, the CARRA dataset has not been produced with such a system, so we will provide overall "static", not "weather dependent", uncertainties.
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Name | Levels |
Pressure | Surface as well as mean sea level |
U-component of wind | Pressure levels (50 - 1000 hPa) |
V-component of windy | Pressure levels (50 - 1000 hPa) |
Temperature | Pressure levels (50 - 1000 hPa) |
Geopotential (East domain only) | Pressure levels (50 - 1000 hPa) |
Relative humidity (East domain)/Specific humidity (West domain) | Pressure levels (50 - 1000 hPa) |
In section 6.5 we present uncertainties measured as statistics of actual deviations from observations (also known as verification statistics). Note that observations are a reference not identical to the actual truth, as they also will have uncertainties as well as representativeness issues. This verification statistics is provided for a set of near-surface quantities which are covered by the meteorological observation network, including 2m temperature, 10m winds and precipitation.
Field based atmospheric uncertainty estimation
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
Surface pressure | sp | Pa | 0m above ground | 37.20 | 26.78 | 41.14 | 38.67 |
Mean sea level pressure | msl | Pa | 0m above sea level | 38.18 | 27.49 | 42.15 | 39.62 |
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Figure 2: Climatological analysis error standard deviation for u-component of wind: summer statistics (left), winter statistics (right) as function of standard vertical pressure levels for the CARRA-East domain.
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
u-component of wind | u | m/s | 50hPa | 0.545 | 0.223 | 0.556 | 0.228 |
u-component of wind | u | m/s | 100hPa | 0.372 | 0.153 | 0.397 | 0.169 |
u-component of wind | u | m/s | 150hPa | 0.584 | 0.239 | 0.619 | 0.254 |
u-component of wind | u | m/s | 200hPa | 0.865 | 0.355 | 0.923 | 0.378 |
u-component of wind | u | m/s | 250hPa | 1.077 | 0.442 | 1.089 | 0.447 |
u-component of wind | u | m/s | 300hPa | 1.290 | 0.530 | 1.240 | 0.508 |
u-component of wind | u | m/s | 400hPa | 1.282 | 0.526 | 1.292 | 0.530 |
u-component of wind | u | m/s | 500hPa | 1.284 | 0.526 | 1.364 | 0.559 |
u-component of wind | u | m/s | 600hPa | 1.322 | 0.648 | 1.392 | 0.738 |
u-component of wind | u | m/s | 700hPa | 1.346 | 0.740 | 1.404 | 0.927 |
u-component of wind | u | m/s | 800hPa | 1.344 | 0.833 | 1.324 | 1.006 |
u-component of wind | u | m/s | 850hPa | 1.331 | 0.865 | 1.274 | 1.045 |
u-component of wind | u | m/s | 900hPa | 1.311 | 0.905 | 1.275 | 1.122 |
u-component of wind | u | m/s | 925hPa | 1.315 | 0.921 | 1.295 | 1.178 |
u-component of wind | u | m/s | 950hPa | 1.330 | 0.958 | 1.305 | 1.227 |
u-component of wind | u | m/s | 1000hPa | 1.302 | 0.937 | 1.172 | 1.102 |
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
v-component of wind | v | m/s | 50hPa | 0.541 | 0.222 | 0.541 | 0.222 |
v-component of wind | v | m/s | 100hPa | 0.376 | 0.154 | 0.384 | 0.157 |
v-component of wind | v | m/s | 150hPa | 0.597 | 0.245 | 0.599 | 0.246 |
v-component of wind | v | m/s | 200hPa | 0.884 | 0.362 | 0.898 | 0.368 |
v-component of wind | v | m/s | 250hPa | 1.105 | 0.453 | 1.061 | 0.435 |
v-component of wind | v | m/s | 300hPa | 1.337 | 0.548 | 1.209 | 0.496 |
v-component of wind | v | m/s | 400hPa | 1.313 | 0.538 | 1.270 | 0.521 |
v-component of wind | v | m/s | 500hPa | 1.328 | 0.544 | 1.351 | 0.554 |
v-component of wind | v | m/s | 600hPa | 1.363 | 0.668 | 1.391 | 0.737 |
v-component of wind | v | m/s | 700hPa | 1.383 | 0.761 | 1.402 | 0.925 |
v-component of wind | v | m/s | 800hPa | 1.382 | 0.857 | 1.332 | 1.012 |
v-component of wind | v | m/s | 850hPa | 1.363 | 0.886 | 1.282 | 1.051 |
v-component of wind | v | m/s | 900hPa | 1.342 | 0.926 | 1.277 | 1.124 |
v-component of wind | v | m/s | 925hPa | 1.344 | 0.941 | 1.293 | 1.177 |
v-component of wind | v | m/s | 950hPa | 1.361 | 0.980 | 1.299 | 1.221 |
v-component of wind | v | m/s | 1000hPa | 1.318 | 0.949 | 1.167 | 1.097 |
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
temperature | t | K | 50hPa | 0.141 | 0.058 | 0.142 | 0.058 |
temperature | t | K | 100hPa | 0.122 | 0.050 | 0.122 | 0.050 |
temperature | t | K | 150hPa | 0.230 | 0.094 | 0.224 | 0.092 |
temperature | t | K | 200hPa | 0.466 | 0.191 | 0.441 | 0.181 |
temperature | t | K | 250hPa | 0.490 | 0.201 | 0.438 | 0.180 |
temperature | t | K | 300hPa | 0.392 | 0.161 | 0.406 | 0.167 |
temperature | t | K | 400hPa | 0.314 | 0.129 | 0.341 | 0.140 |
temperature | t | K | 500hPa | 0.346 | 0.142 | 0.359 | 0.147 |
temperature | t | K | 600hPa | 0.399 | 0.196 | 0.399 | 0.211 |
temperature | t | K | 700hPa | 0.465 | 0.256 | 0.465 | 0.307 |
temperature | t | K | 800hPa | 0.537 | 0.333 | 0.485 | 0.369 |
temperature | t | K | 850hPa | 0.586 | 0.381 | 0.508 | 0.417 |
temperature | t | K | 900hPa | 0.614 | 0.424 | 0.520 | 0.458 |
temperature | t | K | 925hPa | 0.604 | 0.423 | 0.531 | 0.483 |
temperature | t | K | 950hPa | 0.612 | 0.441 | 0.546 | 0.513 |
temperature | t | K | 1000hPa | 0.582 | 0.419 | 0.576 | 0.504 |
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
geopotential | z | m²/s² | 50hPa | 42.17 | 17.29 | 41.54 | 17.03 |
geopotential | z | m²/s² | 100hPa | 41.29 | 16.93 | 40.39 | 16.56 |
geopotential | z | m²/s² | 150hPa | 39.06 | 16.01 | 38.22 | 15.67 |
geopotential | z | m²/s² | 200hPa | 30.34 | 12.44 | 30.41 | 12.47 |
geopotential | z | m²/s² | 250hPa | 29.65 | 12.16 | 29.87 | 12.25 |
geopotential | z | m²/s² | 300hPa | 31.28 | 12.82 | 30.92 | 12.68 |
geopotential | z | m²/s² | 400hPa | 29.68 | 12.17 | 29.56 | 12.12 |
geopotential | z | m²/s² | 500hPa | 27.60 | 11.32 | 27.56 | 11.30 |
geopotential | z | m²/s² | 600hPa | 26.57 | 13.02 | 26.47 | 14.03 |
geopotential | z | m²/s² | 700hPa | 25.99 | 14.29 | 25.93 | 17.11 |
geopotential | z | m²/s² | 800hPa | 25.40 | 15.75 | 25.48 | 19.36 |
geopotential | z | m²/s² | 850hPa | 25.13 | 16.33 | 25.68 | 21.06 |
geopotential | z | m²/s² | 900hPa | 25.40 | 17.53 | 26.80 | 23.58 |
geopotential | z | m²/s² | 925hPa | 25.89 | 18.12 | 27.77 | 25.27 |
geopotential | z | m²/s² | 950hPa | 26.74 | 19.25 | 29.02 | 27.28 |
geopotential | z | m²/s² | 1000hPa | 29.47 | 21.22 | 32.43 | 30.48 |
Table 12: Climatological analysis error standard deviation relative humidity for the CARRA-East domain. Anchor table12 table12
Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
relative humidity | r | % | 50hPa | 0.024 | 0.010 | 1.256 | 0.515 |
relative humidity | r | % | 100hPa | 0.010 | 0.004 | 0.194 | 0.080 |
relative humidity | r | % | 150hPa | 0.040 | 0.016 | 0.425 | 0.174 |
relative humidity | r | % | 200hPa | 0.534 | 0.219 | 1.913 | 0.784 |
relative humidity | r | % | 250hPa | 3.223 | 1.321 | 4.900 | 2.009 |
relative humidity | r | % | 300hPa | 6.153 | 2.523 | 8.861 | 3.633 |
relative humidity | r | % | 400hPa | 8.236 | 3.377 | 12.634 | 5.180 |
relative humidity | r | % | 500hPa | 7.181 | 2.944 | 12.562 | 5.150 |
relative humidity | r | % | 600hPa | 6.819 | 3.341 | 11.824 | 6.267 |
relative humidity | r | % | 700hPa | 6.740 | 3.707 | 11.522 | 7.605 |
relative humidity | r | % | 800hPa | 6.544 | 4.057 | 9.638 | 7.325 |
relative humidity | r | % | 850hPa | 6.118 | 3.977 | 8.194 | 6.719 |
relative humidity | r | % | 900hPa | 5.215 | 3.598 | 6.820 | 6.002 |
relative humidity | r | % | 925hPa | 4.674 | 3.272 | 6.303 | 5.736 |
relative humidity | r | % | 950hPa | 4.285 | 3.085 | 5.767 | 5.421 |
relative humidity | r | % | 1000hPa | 3.477 | 2.503 | 4.277 | 4.020 |
Uncertainties for the CARRA-West model domain
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Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
Surface pressure | sp | Pa | 0m above ground | 26.11 | 7.04 |
Mean sea level pressure | msl | Pa | 0m above sea level | 39.44 | 10.64 |
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Figure 7: Climatological analysis error standard deviation for u-component of wind (left plot) and for v-component of wind (right plot) as function of standard vertical pressure levels for the CARRA-West domain.
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Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
u-component of wind | u | m/s | 50hPa | 0.540 | 0.146 |
u-component of wind | u | m/s | 100hPa | 0.370 | 0.100 |
u-component of wind | u | m/s | 150hPa | 0.447 | 0.121 |
u-component of wind | u | m/s | 200hPa | 0.611 | 0.165 |
u-component of wind | u | m/s | 250hPa | 0.732 | 0.198 |
u-component of wind | u | m/s | 300hPa | 0.871 | 0.235 |
u-component of wind | u | m/s | 400hPa | 0.869 | 0.235 |
u-component of wind | u | m/s | 500hPa | 0.862 | 0.233 |
u-component of wind | u | m/s | 600hPa | 0.887 | 0.240 |
u-component of wind | u | m/s | 700hPa | 0.893 | 0.241 |
u-component of wind | u | m/s | 800hPa | 0.856 | 0.231 |
u-component of wind | u | m/s | 850hPa | 0.831 | 0.224 |
u-component of wind | u | m/s | 900hPa | 0.810 | 0.219 |
u-component of wind | u | m/s | 925hPa | 0.803 | 0.217 |
u-component of wind | u | m/s | 950hPa | 0.799 | 0.216 |
u-component of wind | u | m/s | 1000hPa | 0.773 | 0.209 |
Anchor | ||||
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Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
v-component of wind | v | m/s | 50hPa | 0.535 | 0.144 |
v-component of wind | v | m/s | 100hPa | 0.360 | 0.097 |
v-component of wind | v | m/s | 150hPa | 0.449 | 0.135 |
v-component of wind | v | m/s | 200hPa | 0.603 | 0.162 |
v-component of wind | v | m/s | 250hPa | 0.714 | 0.193 |
v-component of wind | v | m/s | 300hPa | 0.851 | 0.230 |
v-component of wind | v | m/s | 400hPa | 0.853 | 0.230 |
v-component of wind | v | m/s | 500hPa | 0.852 | 0.230 |
v-component of wind | v | m/s | 600hPa | 0.877 | 0.237 |
v-component of wind | v | m/s | 700hPa | 0.884 | 0.239 |
v-component of wind | v | m/s | 800hPa | 0.852 | 0.230 |
v-component of wind | v | m/s | 850hPa | 0.826 | 0.223 |
v-component of wind | v | m/s | 900hPa | 0.801 | 0.216 |
v-component of wind | v | m/s | 925hPa | 0.794 | 0.214 |
v-component of wind | v | m/s | 950hPa | 0.792 | 0.214 |
v-component of wind | v | m/s | 1000hPa | 0.763 | 0.206 |
Anchor | ||||
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Figure 8: Climatological analysis error standard deviation for temperature (left plot) and specific humidity (right plot) as a function of standard pressure levels for the CARRA-West domain.
Anchor | ||||
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Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
temperature | t | K | 50hPa | 0.130 | 0.035 |
temperature | t | K | 100hPa | 0.112 | 0.030 |
temperature | t | K | 150hPa | 0.169 | 0.045 |
temperature | t | K | 200hPa | 0.276 | 0.075 |
temperature | t | K | 250hPa | 0.285 | 0.077 |
temperature | t | K | 300hPa | 0.263 | 0.071 |
temperature | t | K | 400hPa | 0.227 | 0.061 |
temperature | t | K | 500hPa | 0.235 | 0.063 |
temperature | t | K | 600hPa | 0.259 | 0.070 |
temperature | t | K | 700hPa | 0.350 | 0.095 |
temperature | t | K | 800hPa | 0.473 | 0.128 |
temperature | t | K | 850hPa | 0.500 | 0.135 |
temperature | t | K | 900hPa | 0.508 | 0.137 |
temperature | t | K | 925hPa | 0.509 | 0.137 |
temperature | t | K | 950hPa | 0.520 | 0.140 |
temperature | t | K | 1000hPa | 0.542 | 0.146 |
Table 17: Climatological analysis error standard deviation for specific humidity for the CARRA-West domain. Anchor table17 table17
Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
specific humidity | r | g/kg | 50hPa | 0. | 0. |
specific humidity | r | g/kg | 100hPa | 0. | 0. |
specific humidity | r | g/kg | 150hPa | 0. | 0. |
specific humidity | r | g/kg | 200hPa | 0.001 | 0.0002 |
specific humidity | r | g/kg | 250hPa | 0.002 | 0.0004 |
specific humidity | r | g/kg | 300hPa | 0.006 | 0.001 |
specific humidity | r | g/kg | 400hPa | 0.020 | 0.005 |
specific humidity | r | g/kg | 500hPa | 0.048 | 0.013 |
specific humidity | r | g/kg | 600hPa | 0.082 | 0.022 |
specific humidity | r | g/kg | 700hPa | 0.113 | 0.031 |
specific humidity | r | g/kg | 800hPa | 0.127 | 0.034 |
specific humidity | r | g/kg | 850hPa | 0.126 | 0.034 |
specific humidity | r | g/kg | 900hPa | 0.119 | 0.032 |
specific humidity | r | g/kg | 925hPa | 0.115 | 0.031 |
specific humidity | r | g/kg | 950hPa | 0.112 | 0.030 |
specific humidity | r | g/kg | 1000hPa | 0.099 | 0.027 |
Questions & Answers on field uncertainty estimates
For information and "questions and answers" (Q&A) on the uncertainty estimates for the ERA5 host reanalysis used on the lateral boundaries of this Arctic Regional Reanalysis, see this link:
ERA5: uncertainty estimation
The field uncertainty estimates provided here apply a different approach. The below Q&A is similar to the Q&A for the global reanalysis, adapted to apply for the uncertainty estimates provided here (for the Arctic reanalysis).
...
Since the regional reanalysis is run nested into the ERA5 global reanalysis, it is affected by the known issues of ERA5. In addition to those issues, we have found that ERA5 uses incorrect glacier masks for most of the glaciers in the regional Arctic reanalysis domain, and the glaciers in ERA5 always have an analysis albedo of 0.85. This is wrong, since for instance exposed glacier ice albedos during summer are unaccounted for. These areas affect the general circulation and thermodynamic state in ERA5 and can affect the quality of the Arctic regional reanalysis.
Additionally, the Arctic reanalysis has the following known issues:
...
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This document has been produced in the context of the Copernicus Climate Change Service (C3S). The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation Agreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view. |
Definition of the 65 vertical layer structure in HARMONIE
The CARRA vertical coordinate system is a terrain-following hybrid vertical coordinate, which means that it is terrain following at the bottom and pressure based on the top of the atmosphere. It has the advantage to describe the surface terrain properly, but also benefitting the advantage of having the pressure coordinate at the top of the atmosphere.
CARRA uses 65 model levels (level 65 is the surface and level 1 is the top of the atmosphere), which is further splitted into the so called half levels. CARRA has 66 half levels and the pressure of each half level can be obtained by the following formula:
P (k+1/2) = A (k+1/2) + B (k+1/2) * Ps
where k=0.... 65, Ps is surface pressure and the A and B coefficients (see below) valid at each half level.
The full model level pressure [1, 2, ...65] is defined as the mean of the pressure of each pair of neighbouring half levels [0,5, 1.5, ...65.5]. The model variables are defined in the full model levels.
The A and B coefficients are listed below (from the top to the bottom).
'AHALF'=>'0.00000000, 2000.00000000, 4000.21287319, 6002.09662113, 7911.25838577, 9633.01049417,11169.37146237, 12522.57753978, 13695.00149653, 14689.11546998, 15507.49052823, 16154.69697732, 16632.12471208, 16940.14949960, 17082.34869816, 17065.28164099, 16898.18367797, 16592.58939571, 16161.90395878, 15620.94340550, 14985.46502362, 14271.70773051, 13495.95994372, 12674.16909910, 11821.60314859, 10952.57042620, 10080.20053763, 9216.28565403, 8371.17893039, 7553.74479607, 6771.35457397, 6029.92021691, 5333.95880836, 4686.68074804, 4090.09511346, 3545.12645110, 3051.73811264, 2609.05813936, 2215.50455766, 1868.90774223, 1566.62821060, 1305.66882073, 1081.85503306, 890.47596795, 727.74548529, 590.17748096, 474.58767980, 378.08857614, 298.07947335, 232.23312781, 178.48015386, 134.99207440, 100.16369201, 72.59529482, 51.07508967, 34.56216490, 22.17022046, 13.15225964, 6.88641310, 2.86306141, 0.67344356, 0.00000000, 0.00000000, 0.00000000, 0.00000000, 0.00000000
'BHALF'=>'0.00000000, 0.00000000, 0.00000000, 0.00000000, 0.00095468, 0.00382570, 0.00862327, 0.01535782, 0.02404046, 0.03468314, 0.04729839, 0.06195102, 0.07868187, 0.09744325, 0.11815586, 0.14071098, 0.16497348, 0.19078554, 0.21797086, 0.24633925, 0.27569119, 0.30582244, 0.33652825, 0.36760726, 0.39886479, 0.43011564, 0.46118624, 0.49191624, 0.52215946, 0.55178443, 0.58067442, 0.60872709, 0.63585388, 0.66197911, 0.68703898, 0.71098036, 0.73375964, 0.5534143, 0.77569737, 0.79480486, 0.81264598, 0.82920633, 0.84454000, 0.85875505, 0.87191802, 0.88409276, 0.89534045, 0.90571965, 0.91528643, 0.92409452, 0.93219549, 0.93963895, 0.94647277, 0.95274328, 0.95849551, 0.96377340, 0.96862008, 0.97307803, 0.97718944, 0.98099640, 0.98454132, 0.98786727, 0.99102462, 0.99406510, 0.99703923, 1.00000000
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